基於軟體無線電之寬頻無線接取系統設計

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(1)國立交通大學電信工程學系碩士班碩士論文. 基於軟體無線電之寬頻無線接取系統設計 Design of a Software Defined Radio Based Broadband Wireless Access System. 研究生：葉舜文. Student: Shuen-Wen Yeh. 指導教授：李大嵩博士. Advisor: Dr. Ta-Sung Lee. 中華民國九十五年六月.

(2) 基於軟體無線電之寬頻無線接取系統設計 Design of a Software Defined Radio Based Broadband Wireless Access System. 研究生：葉舜文. Student: Shuen-Wen Yeh. 指導教授：李大嵩博士. Advisor: Dr. Ta-Sung Lee. 國立交通大學電信工程學系碩士班碩士論文. A Thesis Submitted to Department of Communication Engineering College of Electrical Engineering and Computer Science National Chiao Tung University in Partial Fulfillment of the Requirements for the Degree of Master of Science in Communication Engineering June 2006. Hsinchu, Taiwan, Republic of China. 中華民國九十五年六月.

(3) 基於軟體無線電之寬頻無線接取系統設計學生：葉舜文. 指導教授：李大嵩博士. 國立交通大學電信工程學系碩士班. 摘要寬頻無線網路即將給人們的生活帶來突破性的變化，不論在何時何地都能以高傳輸速率得到想獲取的資訊。WiMAX (Worldwide Interoperability for Microwave Access; 全球互通的微波存取)，目前已準備好成為新一代的寬頻無線接取技術並可提供固定式及移動式的網路服務。新興的 IEEE 802.16-2005 規格為了在不同的無線傳輸服務達到最佳化，整合了三種空中傳輸介面：單載波模式(Single Carrier, SC)、正交分頻多工模式(Orthogonal Frequency Division Multiplexing, OFDM)及正交分頻多重接取模式(Orthogonal Frequency Division Multiple Access, OFDMA)。在本論文中，吾人將探討 SC-OFDM-OFDMA 三模收發機之共同設計；藉由軟體定義無線電(Software Defined Radio, SDR)概念的引入，吾人設計之收發機架構可在單一平台上有效支援 IEEE 802.16-2005 所定義的三種空中傳輸介面。吾人將探討此共同設計所需之通道估測、時序同步及載波頻率估測等方法；具體而言，吾人將提出共同設計之時序及載波頻率飄移估測法。為了進一步提高系統傳輸的距離及可靠性，吾人在此架構中利用 IEEE 802.16-2005 所定義的多根天線傳輸技術，如時空編碼(Space-Time Coding, STC)及適應性天線系統(Adaptive Antenna System, AAS)等。最後，吾人將藉由電腦模擬驗證所提出之共同設計之 SC-OFDM-OFDMA 收發機架構，在無線通訊環境中具有可靠的傳輸效能，並展示出多根天線傳輸技術可帶來效能的改善。. I.

(4) Design of a Software Defined Radio Based Broadband Wireless Access System Student: Shuen-Wen Yeh. Advisor: Dr. Ta-Sung Lee. Department of Communication Engineering National Chiao Tung University Abstract Broadband wireless will revolutionize people's lives by enabling a high-speed connection directly to the information they need, whenever and wherever they need it. WiMAX (Worldwide Interoperability for Microwave Access) is poised to become a key technical underpinning of fixed, portable and mobile data networks. It’s the development of the emerging IEEE 802.16 standard that integrates Single Carrier (SC), Orthogonal Frequency Division Multiplexing (OFDM) and Orthogonal Frequency Division Multiple Access (OFDMA) for the optimization of different wireless data services. In this thesis, we investigate the joint design of SC-OFDM-OFDMA transceivers on a single platform via the concept of Software Defined Radio (SDR) to support various air-interface standards specified by IEEE 802.16-2005. In this way, the system possesses as many common components as possible for these three modes, and the transmitter and receiver can be switched among the three modes via SDR operation. Synchronization schemes for the SDR system are also investigated in this thesis. In particular, we propose a joint design of timing and frequency synchronization algorithm with lower computational complexity. In order to increase the range and reliability of the system, the use of multiple-antenna techniques such as Space-Time Coding (STC) II.

(5) and Adaptive Antenna Systems (AAS) in IEEE 802.16-2005 is also considered and verified to exhibit improved performance. Finally, we evaluate the performance of the joint design of SC-OFDM-OFDMA SDR system and confirm that it works reliably under the three modes.. III.

(6) Acknowledgement I would like to express my deepest gratitude to my advisor, Dr. Ta-Sung Lee, for his enthusiastic guidance and great patience. I also wish to thank my friends for their encouragement and help. Finally, I would like to show my sincere thanks to my parents for their inspiration and love.. IV.

(7) Contents Chinese Abstract. I. English Abstract. II. Acknowledgement. IV. Contents. V. List of Figures. VIII. List of Tables. XII. Acronym Glossary. XIII. Notations. XVI. Chapter 1 Introduction.................................................................. 1 Chapter 2 Overview of WiMAX System...................................... 5 2.1 Physical Layer Description.................................................................................... 6 2.1.1 Randomizer..................................................................................................... 7 2.1.2 Forward Error Correction ............................................................................... 9 2.1.3 Interleaver ..................................................................................................... 11 2.1.4 Modulator...................................................................................................... 11 2.1.4.1 Pilot Modulation .................................................................................... 12 2.1.4.2 Preamble Structure................................................................................. 12 V.

(8) 2.2 Key Features of Scalable OFDMA...................................................................... 14 2.2.1 Scalable Channel Bandwidth ........................................................................ 14 2.2.2 Sub-channelization and Permutation ............................................................ 16 2.2.3 Fractional Frequency Reuse.......................................................................... 20 2.3 Transmit Techniques ............................................................................................ 21 2.3.1 Transmit Diversity: Space-Time Coding ...................................................... 22 2.3.2 Transmit Beamforming: Adaptive Antenna System ..................................... 25 2.4 Summery.............................................................................................................. 28. Chapter 3 Channel Estimation and Synchronization for WiMAX System ........................................................................................ 30 3.1 Channel Model..................................................................................................... 31 3.1.1 SUI Channel Model for Fixed Wireless Application .................................... 32 3.1.2 ITU Channel Model for Mobile Wireless Application ................................. 36 3.2 Timing and Frequency Synchronization .............................................................. 38 3.3 Channel Estimation.............................................................................................. 42 3.4 Phase Estimation.................................................................................................. 44 3.5 Summary.............................................................................................................. 45. Chapter 4 SC-OFDM-OFDMA SDR Architecture..................... 47 4.1 Concept of Software Defined Radio.................................................................... 48 4.2 SC-OFDM-OFDMA SDR System: Transmitter Architecture ............................. 50 4.3 SC-OFDM-OFDMA SDR System: Receiver Architecture ................................. 56 4.3.1 Timing and Frequency Synchronization Block ............................................ 56 4.3.2 Channel Estimation Block ............................................................................ 60 4.3.3 Phase Estimation Block ................................................................................ 60. VI.

(9) 4.4 Computer Simulations ......................................................................................... 62 4.5 Summary.............................................................................................................. 79. Chapter 5 Conclusion ................................................................. 80 Bibliography............................................................................... 83. VII.

(10) List of Figures Figure 1.1. (a) Conventional multicarrier technique (b) Orthogonal multicarrier modulation technique............................................................................. 2. Figure 2.1. PRBS generator for randomizer ............................................................ 8. Figure 2.2. OFDM randomizer DL initialization vector.......................................... 8. Figure 2.3. OFDMA randomizer DL initialization vector ....................................... 9. Figure 2.4. Convolutional encoder ........................................................................ 10. Figure 2.5. PRBS generator for pilot modulation.................................................. 12. Figure 2.6. DL and network entry preamble structure........................................... 13. Figure 2.7. Frequency domain sequences for all full-bandwidth preambles ......... 13. Figure 2.8. Example of DL preamble for segment 1 ............................................. 14. Figure 2.9. Cluster structure for PUSC.................................................................. 16. Figure 2.10. Allocated subcarriers into subchannels for PUSC .............................. 17. Figure 2.11. Example of mapping OFDMA slots to subchannels and symbols in DL PUSC ................................................................................................... 18. Figure 2.12. Description of a UL PUSC tile............................................................ 18. Figure 2.13. Allocated subcarriers into subchannels for FUSC .............................. 19. Figure 2.14. AMC bin structure............................................................................... 19. Figure 2.15. Description of fractional frequency reuse ........................................... 21. Figure 2.16. Block diagram of STC......................................................................... 22. Figure 2.17. Illustration of Alamouti scheme .......................................................... 23. VIII.

(11) Figure 2.18. Cluster structure for STC PUSC using two antennas.......................... 25. Figure 2.19. Illustration of AAS .............................................................................. 26. Figure 2.20. Generalized AAS zone allocation........................................................ 26. Figure 2.21. AAS zone structure in OFDM mode................................................... 27. Figure 2.22. AAS zone structure in OFDMA mode ................................................ 28. Figure 3.1. Doppler spectrum of SUI channel models .......................................... 34. Figure 3.2. Doppler spectrum of ITU channel models .......................................... 38. Figure 3.3. Matched filter output of the jointly designed algorithm for timing synchronization under ITU Vehicular B channel model (at Eb/N0 = 0 dB) ....................................................................................................... 41. Figure 3.4. MSE of the jointly designed algorithm for frequency synchronization under SUI-3 channel model ................................................................. 41. Figure 3.5. Preamble-aided channel estimation scheme........................................ 42. Figure 3.6. Pilot-aided channel estimation scheme ............................................... 43. Figure 3.7. MSE of the residual frequency offset estimate under SUI-3 channel model ................................................................................................... 45. Figure 4.1. Proposed SC-OFDM-OFDMA SDR transmitter architecture............. 50. Figure 4.2. Proposed SC-OFDM-OFDMA SDR receiver architecture ................. 56. Figure 4.3. Long preamble with CP structure........................................................ 57. Figure 4.4. Operation of computing delay correlation outputs in the case with short preamble............................................................................................... 58. Figure 4.5. Operation of computing delay correlation outputs in the case without short preamble...................................................................................... 58. Figure 4.6. SDR receiver architecture for OFDM mode ....................................... 62. Figure 4.7. SDR receiver architecture for OFDMA mode..................................... 63. Figure 4.8. SDR receiver architecture for SC mode .............................................. 63 IX.

(12) Figure 4.9. BER performance with 256-point FFT with BPSK in OFDM transmission mode under Veh A channel ............................................. 67. Figure 4.10. BER performance with 256-point FFT with QSPK in OFDM transmission mode under Veh A channel ............................................. 67. Figure 4.11. BER performance with 256-point FFT with 16QAM in OFDM transmission mode under Veh A channel ............................................. 68. Figure 4.12. BER performance with 128-point FFT in OFDMA transmission mode under Veh A channel ............................................................................ 69. Figure 4.13. BER performance with 512-point FFT in OFDMA transmission mode under Veh A channel ............................................................................ 70. Figure 4.14. BER performance with 1024-point FFT in OFDMA transmission mode under Veh A channel ............................................................................ 70. Figure 4.15. BER performance with 2048-point FFT in OFDMA transmission mode under Veh A channel ............................................................................ 71. Figure 4.16. MSE of frequency offset estimates in OFDMA-128, 512, 1024 and 2048 mode............................................................................................ 71. Figure 4.17. BER performance with coded QPSK in SC transmission mode under SUI-1 channel ...................................................................................... 72. Figure 4.18. BER performance with coded 16QAM in SC transmission mode under SUI-1 channel ...................................................................................... 73. Figure 4.19. BER performance with STC (2Tx1Rx) and QPSK in OFDMA-2048 mode under Veh A channel .................................................................. 74. Figure 4.20. BER performance with STC (2Tx1Rx) and 16QAM in OFDMA-2048 mode under Veh A channel .................................................................. 74. Figure 4.21. BER performance with STC (2Tx1Rx) and 64QAM in OFDMA-2048 mode under Veh A channel .................................................................. 75 X.

(13) Figure 4.22. BER performance with AAS (4Tx1Rx) and QPSK in OFDMA-2048 mode under Veh A 3km/hr channel...................................................... 76. Figure 4.23. BER performance with AAS (4Tx1Rx) and QPSK in OFDMA-2048 mode under Veh A 120km/hr channel.................................................. 77. Figure 4.24. BER performance with AAS (4Tx1Rx) and 16QAM in OFDMA-2048 mode under Veh A 3km/hr channel...................................................... 77. Figure 4.25. BER performance with AAS (4Tx1Rx) and 16QAM in OFDMA-2048 mode under Veh A 120km/hr channel ................................................. 76. Figure 4.26. BER performance with AAS (4Tx1Rx) and 64QAM in OFDMA-2048 mode under Veh A 3km/hr channel...................................................... 77. Figure 4.27. BER performance with AAS (4Tx1Rx) and 64QAM in OFDMA-2048 mode under Veh A 120km/hr channel.................................................. 77. XI.

(14) List of Tables Table 2.1. Data rate for different modulations and code rates ................................. 6. Table 2.2. Puncturing patterns and serialization orders to realize different........... 10. Table 2.3. Uncoded block size for different modulations and ............................... 10. Table 2.4. OFDMA scalability parameters for different bandwidth ...................... 15. Table 3.1. Parameters of SUI-3 channel models.................................................... 32. Table 3.2. Parameters of ITU channel models....................................................... 37. Table 4.1. Uncoded data block size for SC mode .................................................. 52. Table 4.2. Uncoded data block size for OFDM-256 mode .................................... 53. Table 4.3. Uncoded data block size for OFDMA-2048 mode ............................... 54. Table 4.4. Uncoded data block size for OFDMA-1024 mode ............................... 54. Table 4.5. Uncoded data block size for OFDMA-512 mode ................................. 54. Table 4.6. Uncoded data block size for OFDMA-128 mode ................................. 55. Table 4.7. Number of subchannels in Major Group 0 for different FFT sizes....... 55. Table 4.8. Channel models used in the simulations ............................................... 65. Table 4.9. Simulation parameters for mobile WiMAX.......................................... 65. Table 4.10. OFDMA scalability parameters for different bandwidth ...................... 66. XII.

(15) Acronym Glossary AAS. adaptive antenna system. AMC. adaptive modulation and coding. BER. bit error rate. BPSK. binary phase shift keying. BS. base station. BW. bandwidth. BWA. broadband wireless access. CC. convolutional code. CCIR. co-channel interference rejection. CINR. carrier-to-interference-and-noise ratio. CP. cyclic prefix. DL. downlink. DLFP. downlink frame prefix. FDD. frequency division duplex. FEC. forward error correction. FFT. fast fourier transform. FUSC. full usage of subchannels. ICI. inter carrier interference. IE. information element. IEEE. institute of electrical and electronics engineers. XIII.

(16) IFFT. inverse fast fourier transform. ISI. inter symbol interference. ITU. international telecommunications union. LOS. line-of-sight. MAC. medium access control. MIMO. multiple input multiple output. NLOS. non-line-of-sight. OFDM. orthogonal frequency division multiplexing. OFDMA. orthogonal frequency division multiple access. PHY. physical layer. PRBS. pseudo-random binary sequence. PUSC. partial usage of subchannels. QAM. quadrature amplitude modulation. QoS. quality of service. QPSK. quadrature phase shift keying. RS. reed solomon. Rx. receiver. SC. single carrier. SDR. software defined radio. SNR. signal-to-noise ratio. SOFDMA. scalable orthogonal frequency division multiple access. SP. short preamble. SS. subscriber station. STC. space time coding. TDD. time division duplex. TDMA. time division multiple access XIV.

(17) Tx. transmitter. UL. uplink. WiMAX. worldwide interoperability for microwave access. XV.

(18) Notations Nt. number of transmit antennas. M. number of data subcarriers. L. maximum length of the channel. H. channel frequency response. lLP. known long preamble. ν. correlation window size. Δf. frequency offset between the transmitter and receiver (unit in Hz). Δfr. residual frequency offset (unit in Hz). Ψ. delay correlation outputs. Ψi. timing acquisition metric. qs. phase estimator. N. FFT size. m. modulation order. c. convolutional code rate. NSC. number of subchannels allocated. TFFT. symbol duration of the useful part of the received signal. Tsamp. sampling time. Eb. bit energy. Es. symbol energy. XVI.

(19) Chapter 1 Introduction Wireless communication systems have been in use for quite a long time. Many standards are available based on which these devices communicate, but the present standards fail to provide sufficient data rate, when the user is moving at high speed. Broadband wireless access is an appealing way to provide flexible and easily-deployable solution for high speed communications. In view of this requirement for future mobile wireless communication systems, the 802.16 standard has been proposed by Institute of Electrical and Electronic Engineers (IEEE) [1], [2]. The WiMAX (Worldwide Interoperability for Microwave Access) Forum is committed to providing optimized solutions for fixed, nomadic, portable and mobile broadband wireless access. Two versions of WiMAX address the demand for these different types of access: • IEEE 802.16-2004 (802.16d): This is based on the 802.16-2004 version of the IEEE 802.16 standard. It uses Orthogonal Frequency Division Multiplexing (OFDM) and supports fixed and nomadic access in Line of Sight (LOS) and Non Line of Sight (NLOS) environments. The initial WiMAX Forum profiles are in the 3.5 GHz and 5.8 GHz frequency bands. The first certified products are expected by the end of 2005. • IEEE 802.16-2005 (802.16e): Optimized for dynamic mobile radio channels, 1.

(20) this version is based on the IEEE 802.16-2005 amendment and provides support for handoffs and roaming. It uses Scalable Orthogonal Frequency Division Multiplexing Access (SOFDMA), a multi-carrier modulation technique that uses sub-channelization. Service providers that deploy IEEE 802.16-2005 can also use the network to provide fixed service. The WiMAX Forum has not yet announced the frequency bands for the IEEE 802.16-2005 profiles, but 2.3 GHz and 2.5 GHz are the most likely initial candidates. Broadband wireless communications have a wide bandwidth, which may exceed the coherence bandwidth of the channel. In this case, the fading is likely to be frequency selective, and an equalizer must be used to mitigate the inter symbol interference (ISI). OFDM is a very effective method for combating the frequency selective fading as shown in Figure 1.1. It divides the transmission bandwidth into many narrow band subcarriers and uses these subcarriers to transmit signals in parallel. Since the bandwidth of each subcarrier is smaller than the coherence bandwidth of a multipath fading channel, from the viewpoint of each subcarrier the channel can be regarded as frequency-nonselective. Therefore, OFDM seems to be a good solution for overcoming the ISI due to multipath propagation.. Ch.1 Ch.2 Ch.3 Ch.4 Ch.5 Ch.6 Ch.7 Ch.8 Ch.9 Ch.10. (a). Frequency. Saving of bandwidth. (b). Frequency. Figure 1.1: (a) Conventional multicarrier technique (b) Orthogonal multicarrier modulation technique 2.

(21) Since early 1980, a lot of standards of communication systems have been proposed due to an exponential growing of demands for communication. The industrial competition among Asia, Europe, and North America presents a difficult path toward a unique standard for future mobile systems. This therefore prompts the development of the Software Defined Radio (SDR) concept as a potential practical solution, with a flexible transmitter/receiver architecture, controlled or programmable by software. Broadband, multi-carrier and SDR mobile wireless network infrastructure is directly applicable to the emerging IEEE 802.16 technologies, particularly the IEEE 802.16-2005 mobile high-speed data requirements. OFDM waveforms, as used in the IEEE 802.16 technology, can be very efficiently implemented using Fast Fourier Transform (FFT) techniques to provide significant architecture advantages. This motivates us to investigate the jointly designed scheme for the Single carrier (SC), OFDM and OFDMA transceivers under the SDR system architecture, which is the principle part of this thesis. We aim to combine the transmitter and receiver architectures of the three transmission techniques, SC, OFDM and OFDMA (based on IEEE 802.16-2005 standard), as much as possible under the SDR system architecture. In this way, the transceiver possesses as many common components as possible for SC, OFDM and OFDMA modes, and the transmission mode of the combined transceiver architecture can be switched among the three modes via the concept of SDR operation. Synchronization, channel estimation schemes, and phase estimation scheme for the jointly designed transceiver are also investigated in this thesis. In particular, we propose a jointly designed timing offset and frequency offset estimation scheme with low computational complexity. The jointly designed timing offset and frequency offset estimation scheme is developed based on the common delay correlation outputs. The computational complexity of the proposed synchronization scheme is lower than that of the conventional scheme because the proposed scheme can reuse the same delay 3.

(22) correlation outputs. The rest of this thesis is organized as follows. In Chapter 2, an overview of WiMAX system is given. The transmit techniques such as Space-Time Coding (STC) and Adaptive Antenna System (AAS) are also introduced. In Chapter 3, channel estimation and joint design of timing offset and frequency offset estimation scheme are introduced. The phase estimation and the residual frequency offset estimation are also described, and then computer simulations show that the frequency offset can be corrected more accurately after compensating the residual frequency offset. In Chapter 4, we propose a SC-OFDM-OFDMA SDR system to support the various air-interface standards specified by IEEE 802.16-2005 on a single SDR platform. Some receiver functional blocks will be modified to adapt to different modes. In Chapter 5, we conclude this thesis.. 4.

(23) Chapter 2 Overview of WiMAX System WiMAX is a broadband wireless technology that supports fixed, nomadic, portable and mobile access. To meet the requirements of different types of access, two versions of WiMAX have been defined. The first is based on IEEE 802.16-2004 and is optimized for fixed and nomadic access. The second version is designed to support portability and mobility, and will be based on the IEEE 802.16-2005 amendment to the standard. In this chapter, an overview of WiMAX PHY will be given first. As with IEEE 802.16-2004, IEEE 802.16-2005 will incorporate previous versions of the standard and add support for fixed and mobile access. In this chapter, we will focus on the physical layer of IEEE 802.16-2005 and provide a detail introduction of Scalable OFDMA (SOFDMA) technology. Finally, the transmit techniques such as STC and AAS adopted in the system will be introduced.. 5.

(24) 2.1 Physical Layer Description Worldwide Interoperability of Microwave Access (WiMAX) is a technology based on the IEEE 802.16 specifications to enable the delivery of last mile wireless broadband access as an alternative to cable and DSL. WiMAX will provide fixed, nomadic, and portable mobile wireless broadband connectivity without the requirement for direct line-of-sight with a base station. WiMAX provides metropolitan area network connectivity at speeds of up to 75 Mb/sec. WiMAX systems can be used to transmit signal as far as 30 miles. However, on the average a WiMAX base-station installation will likely cover between three to five miles [3]. WiMAX covers both LOS and NLOS applications in the 2-66 GHz frequencies. The PHY layer contains several forms of modulation and multiplexing to support different frequency range and application. Data rates determined by exact modulation and encoding schemes are shown in Table 2.1. The IEEE 802.16 standard was originally written to support several physical medium interfaces and it is expected that it will continue to develop and extend to support other PHY specifications. Hence, the modular nature of the standard is helpful in this aspect. For example, the first version of the standard only supported single carrier modulation. Since that time, OFDM has been added [4].. Table 2.1: Data rate for different modulations and code rates under different bandwidths. Raw bit rate (Mb/s). Bandwidth (MHz). QPSK, CC3/4. 16QAM, CC3/4. 64QAM, CC3/4. 6. 7.5. 15. 22.5. 7. 8.7. 17.5. 26.1. 20. 24.4. 48.8. 73.2. 6.

(25) In IEEE 802.16-2004, its applications are focused on fixed and nomadic applications in the 2-11 GHz. Two multi-carrier modulation techniques are supported in 802.16-2004: OFDM with 256 carriers and OFDMA with 2048 carriers. In December 2002, Task Group e was created to improve support for combined fixed and mobile operation in frequencies below 6 GHz. Work on the IEEE 802.162005 amendment is completion and has been approved by the IEEE. The new version of the standard introduces support for SOFDMA which allows for a variable number of carriers, in addition to the previously-defined OFDM and OFDMA modes. The carrier allocation in OFDMA modes is designed to minimize the effect of the interference on user devices with omni-directional antennas. Furthermore, IEEE 802.16-2005 offers improved support for Multiple Input Multiple Output (MIMO) and AAS, as well as hard and soft handoffs. It also has improved power-saving capabilities for mobile devices and more extensive security features. Both OFDM- and OFDMA-based products can take advantage of the newly added capabilities [5]. In the following sections, we will introduce the main block diagrams of the transmitter architecture. We put emphasis on OFDM mode and OFDMA mode rather than on SC mode. OFDM mode and OFDMA mode have many common blocks such as randomizer, FEC, interleaver, and modulator, so we will introduce them together and point the differences if necessary.. 2.1.1 Randomizer The randomization is performed on each burst of data on the DL and UL, which means that for each allocation of a data block, the randomizer shall be used independently. For RS and CC encoded data, padding will be added to the end of the transmission block, up to the amount of data allocated minus one byte, which shall be. 7.

(26) reserved for the introduction of a 0x00 tail byte by the FEC. The PRBS generator shall be 1 + X 14 + X 15 as shown in Figure 2.1. Each data byte to be transmitted shall enter sequentially into the randomizer. Preambles are not randomized.. LSB. MSB. Figure 2.1: PRBS generator for randomizer. On the downlink, the randomizer shall be re-initialized at the start of each frame. In OFDM mode, the randomizer shall be re-initialized with the sequence: 100101010000000. At the start of subsequent bursts, the randomizer shall be initialized with the vector shown in Figure 2.2. The frame number used for initialization refers to the frame in which the DL burst is transmitted. In OFDMA mode, the randomizer shall be initialized with the vector shown in Figure 2.3. The subchannel offset used for initialization refers to the allocated subchannels in which the DL burst is transmitted.. Figure 2.2: OFDM randomizer DL initialization vector. 8.

(27) Figure 2.3: OFDMA randomizer DL initialization vector. 2.1.2 Forward Error Correction In OFDM mode, the encoding is performed by first passing the data in block format through RS encoder and then passing it through a convolutional encoder. A single 0x00 tail byte is appended to the end of each burst after randomization. The Reed-Solomon encoding shall be derived from a systematic RS (N = 255, K = 239, T = 8) code using GF(28), where N is the number of overall bytes after encoding, K is the number of overall bytes before encoding, and T is the number of data bytes that can be corrected. Each RS block is encoded by the binary convolutional encoder, which shall have native rate of 1/2, a constraint length equal to 7, and shall use the generator depicted in Figure 2.4. Puncturing patterns and serialization order that shall be used to realize different code rates are defined in Table 2.2. The RS-CC rate 1/2 shall always be used to as the coding mode when requesting access to the network. Table 2.3 gives the block sizes and the code rates used for the different modulations. In the case of BPSK modulation, the RS encoder shall be bypassed.. 9.

(28) Figure 2.4: Convolutional encoder. Table 2.2: Puncturing patterns and serialization orders to realize different code rates. Table 2.3: Uncoded block size for different modulations and code rates. 10.

(29) In OFDMA mode, the encoding is performed by passing the data block through a convolutional encoder. Its convolutional encoder is the same as OFDM mode. The RS encoder shall be dismissed in OFDMA mode.. 2.1.3 Interleaver All encoded data bits shall be interleaved by a block interleaver with a block size corresponding to the number of coded bits over the allocated subchannels per OFDM symbol. The interleaver is defined by two step permutation. The first permutation ensures that adjacent coded bits are mapped onto nonadjacent subcarriers. The second permutation ensures that adjacent coded bits are mapped alternately onto less or more significant bits of the constellation, thus avoiding long runs of lowly reliable bits.. 2.1.4 Modulator After bit interleaving, the data are entered serially to the constellation mapper. For OFDM mode, BPSK, Gray-mapped QPSK, and 16QAM are mandatory. The constellations shall be normalized by multiplying the constellation point with the indicated factor c to achieve equal average power. The constellation-mapped data shall be subsequently modulated onto all allocated data subcarriers in order of increasing frequency offset index. For OFDMA mode, Gray-mapped QPSK, 16QAM, and 64QAM shall be supported. The constellation-mapped data shall be subsequently modulated onto all allocated data subcarriers and each subcarrier multiplied by the factor 2*(1/ 2 − wk ) according the subcarrier index, k.. 11.

(30) 2.1.4.1 Pilot Modulation Pilot subcarriers shall be inserted into each data burst in order to constitute the symbol and they shall be modulated according to their carrier location within the symbol. The PRBS generator depicted in Figure 2.5 shall be used to produce a sequence, wk . The polynomial for the PRBS generator shall be 1 + X 9 + X 11 . For OFDM mode, each pilot is BPSK modulated and located at the fixed locations in each symbol. For OFDMA mode, each pilot shall be transmitted with a boosting of 2.5 dB over the average power of each data tone. The pilot subcarriers shall be modulated according to Equation (2.1):. 8 1 Re {ck } = ( − wk ) and Im {ck } = 0 3 2. (2.1). The pilot in DL preamble shall be modulated according to Equation (2.2): 1 Re { premablePilotsModulated } = 4 ⋅ 2 ⋅ ( − wk ) 2 Im { premablePilotsModulated } = 0. (2.2). Figure 2.5: PRBS generator for pilot modulation. 2.1.4.2 Preamble Structure For OFDM mode, all preambles are structured as either one or two OFDM symbols. Each of those OFDM symbols contains a CP, which length is the same as the CP for data OFDM symbols. The time domain structure is exemplified in Figure 2.6. The frequency domain sequences for all full-bandwidth preambles are derived from the 12.

(31) sequence as shown in Figure 2.7. The frequency domain sequence for the 4 times 64 sequence P4×64 is defined by Equation (2.3):. ⎧⎪ 2 ⋅ 2 ⋅ conj ( PALL (k )) P4×64( k ) = ⎨ 0 ⎪⎩. kmod 4 = 0 kmod 4 ≠ 0. (2.3). The frequency domain sequence for the 2 times 128 sequence Peven is defined by Equation (2.4): ⎧⎪ 2 ⋅ PALL (k ) Peven ( k ) = ⎨ 0 ⎪⎩. kmod 2 = 0 kmod 2 ≠ 0. (2.4). Figure 2.6: DL and network entry preamble structure. Figure 2.7: Frequency domain sequences for all full-bandwidth preambles. For OFDMA mode, the first symbol of the DL transmission is the preamble and the preamble subcarriers are divided into three carrier-sets. Those subcarriers are modulated using a boosted BPSK modulation with a specific PN code. There are three possible groups consisting of a carrier-set each that may be used by any segment. Each segment uses a preamble composed of a carrier-set out of the three available carrier-sets in the following manner: (In the case of segment 0 under 2048-FFT, the DC carrier will 13.

(32) not be modulated at all and the appropriate PN will be discarded; therefore, DC carrier shall be always zero. For the preamble symbol, there will be 172 guard band subcarriers on the left side and the right side of the spectrum). For example, Figure 2.8 depicts the preamble of segment 1 for 2048-FFT.. Figure 2.8: Example of DL preamble for segment 1. 2.2 Key Features of Scalable OFDMA Although IEEE 802.16-2005 is generally perceived as the mobile version of the standard, in reality it serves the dual purpose of adding extensions for mobility and including new enhancements to the OFDMA physical layer. This new enhanced IEEE 802.16-2005 physical layer is now being referred to as Scalable OFDMA (SOFDMA) and includes a number of important features for fixed, nomadic, and mobile networks. Because of these advantages, most of the industry will build their IEEE 802.16-2005 products using SOFDMA technology. However, the IEEE 802.16-2005 standard is not just for mobility. There are also many compelling reasons for using SOFDMA in fixed broadband wireless access (BWA) networks. In this section, we will focus on some key features of SOFDMA for fixed and mobile wireless applications [6], [7].. 2.2.1 Scalable Channel Bandwidth Scalability is one of the most important advantages of OFDMA. Spectrum resources for wireless broadband worldwide are still quite different in its allocation. With OFDMA subcarrier structure, it is designed to be able to scale to work in different. 14.

(33) channelization from 1.25 to 20 MHz to cope with varied worldwide requirements as efforts proceed to achieve spectrum harmonization in the longer term. The scalability is supported by adjusting FFT size according to the different channel bandwidth to fix the subcarrier frequency spacing. By fixing the subcarrier spacing and symbol duration, the basic unit of physical resource is fixed. Therefore, the impact to higher layers is minimal when scaling the bandwidth. The significant advantage from scalability is the flexibility of deployment. With the little modification to different air interfaces, OFDMA system can be deployed in various frequency bands to flexibly address the requirement for various spectrum allocation and usage model requirements. The OFDMA scalability parameters used in the thesis are listed in Table 2.4. The subcarrier spacing is fixed to 11.16 kHz and the symbol time is fixed to 89.6 us. With the flexibility to support wider range bandwidth, OFDMA also enjoys high sector throughput, which allows more efficient multiplexing of data traffic, lower latency and better QoS.. Table 2.4: OFDMA scalability parameters for different bandwidth Parameters. Values. Bandwidth (MHz). 1.25. 2.5. 5. 10. 20. Sampling frequency (MHz). 1.43. 2.86. 5.71. 11.4. 22.8. FFT size. 128. 256. 512. 1024. 2048. Subcarrier spacing. 11.16 KHz. Useful symbol time (Tb). 89.6 us. CP duration. 22.4 us (Tb/4). 15.

(34) 2.2.2 Sub-channelization and Permutation Active (data and pilot) subcarriers are grouped into subsets of subcarriers called subchannels. The OFDMA PHY supports sub-channelization in both DL and UL. The minimum frequency-time resource unit of sub-channelization is one slot, which is equal to 48 data tones. There are two major types of subcarriers permutation for subchannelization: diversity and contiguous. The diversity permutation takes subcarriers pseudo-randomly to form a subchannel. The diversity permutations include DL & UL PUSC (Partial Usage of Subchannels), DL FUSC (Full Usage of Subchannels), and additional optional permutations. The contiguous permutation groups a block of adjacent sub-carriers to form a subchannel. The contiguous permutations include DL & UL AMC (Adaptive Modulation and Coding). With DL PUSC, for each pair of OFDM symbols, the usable subcarriers are grouped into clusters containing 14 adjacent subcarriers per symbol, with pilot and data allocations in each cluster in the even and odd symbols as shown in Figure 2.9.. subcarriers. Figure 2.9: Cluster structure for PUSC. Divide these clusters into several Major Groups. The allocation algorithm varies with FFT sizes. For each subchannel, subcarriers are distributed in some clusters that belong to its major group as shown in Figure 2.10. A subchannel contains 2 clusters and is comprised of 48 data subcarriers and 8 pilot subcarriers. Allocating subcarriers to subchannel in each major group is performed separately for each OFDMA symbol by first allocating the pilot carriers within each cluster, and then taking all remaining data 16.

(35) carriers within the symbol and using the procedure described in Equation (2.5): subcarrier (k , s ) =. (2.5). N subchannels ⋅ nk + { ps [nk mod N subchannels ] + DL _ PermBase} mod N subchannels. where subcarrier (k , s ) is the subcarrier index k in subchannel s N subchannels is the number of subchannels in current partitioned major group nk = (k + 13 ⋅ s) mod N subccarriers N subccarriers is the number of data subcarriers allocated to a subchannel ps [ j ] is the series obtained by rotating basic permutation sequence cyclically to the left s times The parameters vary with FFT sizes. Figure 2.11 shows an example of mapping OFDMA slots into subchannels and symbols in the DL PUSC.. Group 0. Group 0. Ng guard subcarriers subcarriers. …. …. Group 0. …. Ng-1 guard subcarriers. subcarriers …. …. Sub-channel 0. … … Sub-channel 1. Figure 2.10: Allocated subcarriers into subchannels for PUSC. 17.

(36) OFDMA symbol index. Spanning two OFDMA symbols. Subchannel number. Figure 2.11: Example of mapping OFDMA slots to subchannels and symbols in DL. PUSC. Compared with the cluster structure for DL PUSC, a tile structure is defined for the UL PUSC whose format is shown in Figure 2.12. The slot is comprised of 48 data subcarriers and 24 pilot subcarriers in 3 OFDM symbols.. Figure 2.12: Description of a UL PUSC tile. FUSC achieves full diversity by spreading tones over entire band. The symbol structure is constructed using pilots, data, and zero subcarriers. The symbol is first allocated with the appropriate pilots and with zero subcarriers, and then all the remaining subcarriers are used as data subcarriers. To allocate the data subchannels, the remaining subcarriers are partitioned into groups of contiguous subcarriers. Each. 18.

(37) subchannel consists of one subcarrier from each of these groups as shown in Figure 2.13. The number of groups is therefore equal to the number of subcarriers per subchannel. The exact partitioning into subchannels is according to the same procedure as Equation (2.5).. Group 0. Group 1. Group 2. Group 3. Group N. Ng guard subcarriers. Ng-1 guard subcarriers. subcarriers. Sub-channel 0. Sub-channel 1. Figure 2.13: Allocated subcarriers into subchannels for FUSC. The contiguous permutation groups a block of adjacent subcarriers to form a subchannel, such as DL AMC and UL AMC. As shown in Figure 2.14, a bin consists of 9 adjacent subcarriers in a symbol, with 8 tones for data and one assigned for a pilot. A slot in AMC is defined as a collection of bins of the type (N x M = 6), where N is the number of adjacent bins and M is the number of adjacent symbols. Thus 4 different ways of defining a slot are (6 bins, 1 symbol), (3 bins, 2 symbols), (2 bins, 3 symbols), (1 bin, 6 symbols). AMC permutation enables multi-user diversity by choosing the sub-channel with the best channel frequency response.. Figure 2.14: AMC bin structure. 19.

(38) In general, diversity subcarrier permutations perform well in mobile applications while contiguous subcarrier permutations are well suited for fixed, portable, or low mobility environments. These options enable the system designer to trade-off mobility for throughput.. 2.2.3 Fractional Frequency Reuse In OFDMA mode, users operate on subchannels which only occupy a small fraction of the channel bandwidth and the cell edge interference problem can be easily solved by reconfiguration of the subchannel usage without resorting to traditional frequency planning. In mobile applications, the flexible subchannel reuse is facilitated by subchannel segmentation and permutation zone. A segment is a subdivision of the available OFDMA subchannels (one segment may include all subchannels). Permutation Zone is a number of contiguous OFDMA symbols in DL or UL that use the same permutation. The DL or UL subframe may contain more than one permutation zone. The subchannel reuse pattern can be configured so that users close to the base station operate on the zone with all subchannels available. While for the edge users, each cell and sector operates on the zone with a fraction of all subchannels available. In Figure 2.15, F1, F2 and F3 are different sets of subchannels in the same frequency channel. With this configuration, the full load frequency reuse of one is maintained for center users to maximize spectral efficiency while fractional frequency reuse is achieved for edge users to improve edge user connection quality and throughput. The subchannel reuse planning can be dynamically optimized across sectors or cells based on network load and interference conditions on a frame by frame basis. All the cells and sectors therefore, can operate on the same frequency channel without the. 20.

(39) requirement for frequency planning.. Figure 2.15: Description of fractional frequency reuse. 2.3 Transmit Techniques In order to increase the range and reliability of WiMAX systems, the WiMAX standard supports optional multiple-antenna techniques such as Alamouti Space-Time Coding (STC), Adaptive Antenna Systems (AAS) and Multiple-Input Multiple-Output (MIMO) systems. There are several advantages to using multiple-antenna technology over single-antenna technology: • Array Gain: This is the gain achieved by using multiple antennas so that the signal adds coherently. • Diversity Gain: This is the gain achieved by utilizing multiple paths so that the probability that any one path is bad does not limit performance. Effectively, diversity gain refers to techniques at the transmitter or receiver to achieve multiple “looks” at the fading channel. These schemes improve performance by increasing the stability of the. 21.

(40) received signal strength in the presence of wireless signal fading. Diversity may be exploited in the spatial (antenna), temporal (time), or spectral (frequency) dimensions. • Co-channel Interference Rejection (CCIR): This is the rejection of signals by making use of the different channel response of the interferers.. 2.3.1 Transmit Diversity: Space-Time Coding In order to increase the rate and range of the modem, there are several considerations. Generally, BS can bear more cost and complexity than SS, so multiple-antenna techniques are a good option at BS, also called transmit diversity. Among various transmit diversity schemes, STC is the most popular scheme with the feature of open loop (i.e., no feedback signaling is required) as channel information is not required at the transmitter. Therefore we will focus on the scheme of STC with 2 transmit antennas in this section as shown in Figure 2.16.. Subchhannel annel Sub-c Modulation Modulation. IFFT IFFT Input Input Packing Packing. #. IFFT IFFT. Filter Filter. DAC DAC. RF RF. IFFT IFFT. Filter Filter. DAC DAC. RF RF. Space-Time Space-Time Encoder Encoder. BS. RF RF. ADC ADC. Filter Filter. FFT FFT. #. Equalizer Equalizer. #. Space-Time Space-Time Decoder Decoder. SubSubchannel channel Demod. Demod.. SS. Figure 2.16: Block diagram of STC. The space-time block coding scheme was first discovered by Alamouti for two transmit antennas. Symbols transmitted from those antennas are encoded in both space and time in a simple manner to ensure that transmissions from both the antennas are orthogonal to each other. This would allow the receiver to decode the transmitted. 22.

(41) information with a slight increment in the computational complexity.. Alamouti scheme ST Encoder. ST Decoder. ∗ ⎡s1⎤ ⎡⎢s1 −s2 ⎤⎥ ⎢ ⎥ 6⎢ ⎢⎣s2⎥⎦ ⎢s s∗ ⎥⎥ ⎣2 1⎦. s. y Hs + n. H. H y = HH Hs + HH n. (. 2. (HH H = h1 + h2. 2. )I. 2. = ρI2 ). Figure 2.17: Illustration of Alamouti scheme. Figure 2.17 shows the operation of Alamouti scheme. The input symbols to the space-time block encoder are divided into groups of two symbols. At a given symbol period, the encoder takes a block of two modulated symbols s1 and s2 in each encoding operation and maps them to the transmit antennas according to a code matrix given by ⎡s −s * ⎤ 2⎥ ⎢ 1 s=⎢ * ⎥ ⎢s2 s1 ⎥ ⎣ ⎦. (2.6). The encoder outputs are transmitted in two consecutive transmission periods from two transmit antennas. Let h1 and h2 be the channel gains from the first and second transmit antennas to the only one receiver antenna. Assume that h1 and h2 are scalar and constant over two consecutive symbol periods. The received signals in two consecutive symbol periods, denoted as r1 and r2, can be expressed as r1 = h1s1 + h2s2 + n1. (2.7). r2 = −h1s2* + h2s1* + n2. where n1 and n2 are AWGN noise modeled as identical independent distributed (i.i.d.). 23.

(42) complex Gaussian random variables with zero mean and power spectral density N0/2 for each dimension. The above equation can be rewritten in a matrix form as h2 ⎤ ⎡s ⎤ ⎡n1 ⎤ ⎡ r1 ⎤ ⎡⎢ h1 ⎥ ⎢ 1⎥ ⎢ ⎥ ⎢ ⎥ + = H⋅s + n r = ⎢ *⎥ = ⎢ * *⎥ s ⎢⎣ 2 ⎥⎦ ⎢n2* ⎥ ⎢⎣r2 ⎥⎦ ⎢⎣⎢(h2 ) −(h1 ) ⎥⎦⎥ N ⎢⎣N⎥⎦ s n. (2.8). H. 2. 2. Since the channel matrix H is unitary, i.e. H H H = ρ·I2, where ρ = h1 + h2 , the ML decoder can perform an MRC operation on the modified signal vector r given by H. H. r = H ⋅ r = ρ ⋅ s + H ⋅ n. n. = ρ⋅s+n. (2.9). Therefore, we can obtain the space-time decoded vector s . In OFDM-256 mode, the preamble for Alamouti transmission is transmitted from both antennas with the even subcarriers used for antenna 1 and the odd subcarriers used for antenna 2. This means that each set of data requires to be appropriately smoothed. The pilots have certain degenerate situations: for the first Alamouti transmitted symbol, the pilots destructively add and for the second Alamouti transmitted symbol, the pilots constructively add. Hence, the pilots cannot always be useful. Properly processing the pilot symbols is required. For OFDMA mode, STC coding is done on all data subcarriers that belong to an STC coded burst in the two consecutive OFDMA symbols. Pilot subcarriers are not encoded and are transmitted from either antenna 0 or antenna 1. In PUSC, the pilot allocation to cluster is changed as shown in Figure 2.18. The pilot locations change in period of 4 symbols to accommodate two antennas transmission with the same estimation capability.. 24.

(43) Figure 2.18: Cluster structure for STC PUSC using two antennas. 2.3.2 Transmit Beamforming: Adaptive Antenna System Future wireless communication systems are aimed to provide higher data rates with better link quality subject to being interference limited. Smart antenna technology is one of the most promising technologies for increasing both system coverage and capacity as shown in Figure 2.19. AAS, although an optional feature, through the use of more than one antenna elements at BS, can significantly improve range and capacity by adapting the antenna pattern and concentrating its radiation to each individual user. There are several advantages of using beamforming: • Increase spectral efficiency proportional to the number of antenna elements • Realize an inter-cell frequency reuse of one and an in-cell reuse factor proportional to the number of antenna elements • Reduce interference by steering nulls in directions of co-channel interferers • Increase SNR of certain subscribers and steer nulls to others that can enable bursts to be concurrently transmitted to spatially separated users.. 25.

(44) Figure 2.19: Illustration of AAS. First, the generalized AAS zone allocation is introduced as shown in Figure 2.20. The frame is divided into two parts: the fist part is allocated to the non-AAS users and the second part (called AAS zone) is allocated to the AAS users. This allows a mixture of non-AAS and AAS users to be supported by the same BS. The BS can dynamically allocate capacity to non-AAS and AAS traffic. The SS without AAS capability will ignore the traffic in the AAS zone. In the following paragraphs, we will introduce the AAS operations for OFDM mode and OFDMA mode individually. Regular DL Bursts. Regular UL Bursts. TDD Regular DL Bursts. DL FDD. Regular UL Bursts. UL. Figure 2.20: Generalized AAS zone allocation. 26.

(45) OFDM Figure 2.21 shows the AAS zone structure in OFDM mode. AAS preamble consists of two OFDM symbols, which can be transmitted from up to four beams. For a SS to distinguish one beam from another, the 200 subcarriers are divided into four groups, with each group transmitted on one beam. Supposing that the 200 subcarriers are represented by their frequency offset index, k, relative to the central carrier, ie, k=-100,-99,…,-2,-1,1,2,…,99,100, the AAS preamble transmitted on beam m, m=0,1,2,3, is defined as those subcarriers with k mod 4. The AAS preamble is used by AAS SS to perform channel estimation on each beam. Each DL burst starts with one or several repetitions of a preamble plus FCH pair. The FCH contains the information about location and transmission parameters for the data burst. This pair may be transmitted on a directed beam, or optionally transmitted on several beams to improve the reliability of the FCH reception. Operation of AAS requires feedback of channel state information. For OFDM mode, AAS-FBCK-REQ is used for assisting beamforming and SS performs the measurement from AAS preamble that belongs to its burst. AAS-BEAM-REQ is used for beam adjustment and SS performs the measurement on specified beams requested by BS.. P re a m b le. A A S -F C H. P re a m b le. A A S -F C H. P re a m b le. AAS P re a m b le. …. A A S -F C H. Directed Beam. Optional diversity zone. DL Burst 1. …. Figure 2.21: AAS zone structure in OFDM mode. 27. AAS UL Zone.

(46) OFDMA Figure 2.22 shows the AAS zone structure in OFDMA mode. AAS_DLFP in an AAS zone is preceded by an AAS DL preamble of one symbol duration. All other data bursts within an AAS zone have a preamble whose duration is specified in AAS_DL_IE. AAS_DLFP provides a robust transmission of required BS parameters to enable SS access allocation. Each AAS_DLFP requires not carry the same information. Different beams may be used within the AAS diversity map zone. For OFDMA mode, REP-RSP MAC message shall be sent by SS in response to a REP-REQ message from the BS to report estimation of the mean DL CINR (carrier-to-interference-and-noise ratio). AAS portion. Non AAS portion. SS #1. SS #2. SS #4. SS #3 Frequency. SS #5. …. AAS_DLFP. 2 OFDMA subchannels. AAS Diversity Map Zone. Time AAS DL preamble. Figure 2.22: AAS zone structure in OFDMA mode. 2.4 Summery Specification of IEEE 802.16 system has been introduced in this chapter. Unlike the CDMA-based 3G systems, which have evolved from voice-centric systems, WiMAX is designed to meet the requirements necessary for the delivery of broadband data services as well as voice. The Mobile WiMAX physical layer is based on Scalable OFDMA technology. The new technologies employed for Mobile WiMAX result in lower equipment complexity and simpler mobility management due to the all-IP core 28.

(47) network and provide Mobile WiMAX systems with many advantages over CDMA based 3G systems. We also introduce some key transmit techniques and their operations. By using these transmit techniques, the capacity and range of the system can be improved significantly.. 29.

(48) Chapter 3 Channel Estimation and Synchronization for WiMAX System In this chapter, channel estimation and synchronization schemes are introduced. In real situations, synchronization and channel estimation should be done before data detection. First, two channel models corresponding to static or mobile environments are introduced in Section 3.1. Second, a jointly designed timing and frequency synchronization scheme is proposed in Section 3.2 and then computer simulations will be showed to confirm the performance of the proposed scheme. In Section 3.3, two channel estimation schemes are introduced to deal with different environments. Finally, Section 3.4 will describe the phase estimation and the residual frequency offset estimation scheme, and then computer simulations show that more accurate frequency synchronization can be obtained after compensating the residual frequency offset.. 30.

(49) 3.1 Channel Model Wireless propagation channels have been studied for more than 50 years, and a large number of channel models are already available. The signal that has propagated through a wireless channel consists of multiple echoes of the originally transmitted signals; this phenomenon is known as multipath propagation. The different multipath components are characterized by different attenuations and delays. The correct modeling of the parameters describing the multipath components is the key point of channel modeling. In first generation systems, a super-cell architecture is used where the base station and subscriber station are in LOS condition and the system uses a single cell with no co-channel interference. For second generation systems, a scalable multi-cell architecture with NLOS conditions becomes necessary. In WiMAX system, the wireless channel is characterized by: ¾. Path loss (including shadowing). ¾. Multipath delay spread. ¾. Fading characteristics. ¾. Doppler spread. The main channel models were considered here: Stanford University Interim (SUI) channel models [11] and International Telecommunication Union (ITU) channel models [12]. Each channel model was parameterized in order to best fit the particular channel characteristics. SUI channel models can be used for simulations, design, and testing of technologies suitable for fixed broadband wireless applications. However, ITU channel models are applied for the measurement based channel model. Even though multipath parameters are fixed in a measurement based channel model, it is useful to reflect the real operating channel conditions.. 31.

(50) 3.1.1 SUI Channel Model for Fixed Wireless Application SUI channel models were proposed in [11] to model a statistic environment in IEEE 802.16d. There are many possible combinations of parameters to obtain different channel descriptions. A set of 6 typical channels were selected for the three terrain types that are typical of the continental US. The channel parameters are related to terrain type, delay spread, and antenna directionality and each channel model has three taps with distinct K-factor and average power. Table 1 shows an example of time domain attribute of the SUI-3 channel, which is chosen to evaluate the proposed algorithm.. Table 3.1: Parameters of SUI-3 channel models. Multipath Delay Profile Due to the scattering environment, the channel has a multipath delay profile. It is characterized by τ rms (RMS delay spread of the entire delay profile) which is defined as 2 τ rms = ∑ j Pjτ 2j − (τ avg ) 2. (3.1). 32.

(51) where. τ avg = ∑ j Pjτ j , τ j is the delay of the jth delay component of the profile and Pj is given by Pj = (power in the jth delay component) / (total power in all components). RMS delay spread A delay spread model was based on a large body of published reports. It was found that the RMS delay spread follows lognormal distribution and that the median of this distribution grows as some power of distance. The model was developed for rural, suburban, urban, and mountainous environments. The model is of the following form. τ rms = T1d ε y. (3.2). where τ rms is the RMS delay spread, d is the distance in km, T1 is the median value of τ rms at d = 1 km, ε is an exponent that lies between 0.5-1.0, and y is a lognormal variant. Depending on the terrain, distance, antenna directivity and other factors, the RMS delay spread values can span from very small values (tens of nanoseconds) to large values (microseconds).. Fading distribution, K-factor The narrow band received signal fading can be characterized by a Ricean fading. The key parameter of this distribution is the K-factor, defined as the ratio of the “fixed” component power and the “scatter” component power. The narrow band K-factor distribution was found to be lognormal, with the median as a simple function of season, antenna height, antenna beamwidth and distance. The model for the K-factor (in linear scale) is as follows:. K = Fs Fh Fb K o d γ u. (3.3). 33.

(52) where. Fs is a season factor; Fs =1.0 in summer; 2.5 in winter Fh is the received antenna height factor Fb is the beamwidth factor K o and γ are regression coefficients u is a lognormal variable which has 0 dB mean and a standard deviation of 8 dB.. Using this model, one can observe that the K-factor decreases as the distance increases and as antenna beamwidth increases.. Doppler spectrum The random components of the coefficients generated in the previous paragraph have a white spectrum since they are independent of each other. The SUI channel model defines a specific power spectral density (PSD) function for these scatter component channel coefficients called “rounded” PSD which is given as ⎧1 − 1.72 f 02 + 0.785 f 04 S( f ) = ⎨ 0 ⎩. where f 0 =. f0 ≤ 1. (3.4). f0 > 1. f . In fixed wireless channels the shape of the spectrum is therefore fm. different than the classical Jake’s spectrum for mobile channels. Figure 3.1 shows that its shape of Doppler spectrum is convex.. Figure 3.1: Doppler spectrum of SUI channel models 34.

(53) Antenna correlation The SUI channel models define an antenna correlation, which has to be considered if multiple transmit or receive elements, i.e. multiple channels, are being simulated. Antenna correlation is commonly defined as the envelope correlation coefficient between signals transmitted at two antenna elements. The received baseband signals are modeled as two complex random processes X(t) and Y(t) with an envelope correlation coefficient of. ρ env =. {( X − E { X }) (Y − E {Y }) } E { X − E { X } } E { Y − E {Y } } ∗. E. 2. 2. (3.5). Note that this is not equal to the correlation of the envelopes of two signals, a measure that is also used frequently in cases where no complex data is available.. Antenna gain reduction factor The use of directional antennas requires to be considered carefully. The gain due to the directivity can be reduced because of the scattering. The effective gain is less than the actual gain. This factor should be considered in the link budget of a specific receiver antenna configuration. Denote ΔGBW as the Gain Reduction Factor. This parameter is a random quantity which dB value is Gaussian distributed with a mean μ grf and a standard deviation. σ grf given by μ grf = −(0.53 + 0.1I) ln( β / 360) + (0.5 + 0.04I)( ln( β / 360))2. (3.6). σ grf = −(0.93 + 0.02I) ln( β / 360). (3.7). where. β is the beamwidth in degrees I = 1 for winter and I = -1 for summer 35.

(54) In the link budget computation, if G is the gain of the antenna (dB), the effective gain of the antenna equals G − ΔGBW . For example, if a 20-degree antenna is used, the mean value of ΔGBW would be closed to 7 dB.. 3.1.2 ITU Channel Model for Mobile Wireless Application As we know, for fixed wireless application such as IEEE 802.16-2004, the SUI channel models are recommended for simulation. However, for mobile wireless application like IEEE 802.16-2005, the recommendatory channel model is not proposed at present. Here we choose International Telecommunication Union (ITU) channel model [12] for mobile and fixed use. ITU channel model is a measurement based channel model proposed for the 3GPP WCDMA system. Delay and average power of each multipath for the ITU channel models are summarized in Table 3.2. Four or six multipath signals are generated in the wireless channel depending on the channel type as shown in Table 3.2 respectively. The ITU channel model can be modeled as w(t ) =. N. ∑. n=1. pn g n (t ) z (t − τ n ). (3.8). where z(t) and w(t) denote the complex low pass representations of the channel input and output respectively, pn is the strength of the nth weight and g n (t) is the complex Gaussian process weighting the nth replica.. 36.

(55) Table 3.2: Parameters of ITU channel models. As shown in Table 3.2, ITU channel model includes two environments. For the pedestrian test environment, this environment is characterized by small cells and low transmit power. Base stations with low antenna height are located outdoors, and pedestrian users are located on streets, inside buildings or residences. Its path loss is defined by L = 40log10 R + 30log10 f + 49. (dB). (3.9). where R denotes the separation (km) between the base station and the mobile station and f is carrier frequency. For vehicular environment, it is characterized by large cells and higher transmit power. The model is applicable for in urban and suburban areas outside the high rise core where the buildings are of nearly uniform height. Its path loss is written as L = 40 (1 − 4 × 10−3 Δhb )log10 R − 18log10 Δhb + 21log10 f + 80. (dB). (3.10). where R is the separation (km) between base station and mobile station f is carrier frequency Δhb is base station antenna height (m), measured from the average rooftop level 37.

(56) The path loss model is valid for a range of Δhb from 0 to 50 m. The ITU channel model uses Doppler spectrum of classical Jake’s spectrum. As shown in Figure 3.2, the Doppler spectrum is concave.. Figure 3.2: Doppler spectrum of ITU channel models. 3.2 Timing and Frequency Synchronization A joint design of timing and frequency synchronization scheme is proposed in this section [13], [14]. Synchronization should be done before the rest work like channel estimation and data detection. Here, we consider three steps to complete the timing and frequency synchronization: (i) adjust the window size according to the known preamble structure and compute the delay correlation outputs; (ii) use the delay correlation outputs to perform the timing synchronization; (iii) use the corresponding delay correlation outputs to perform the frequency synchronization. Before performing the timing and frequency synchronization algorithms, the received signal is passed through a matched filter. The delay correlation outputs can be obtained by correlating the received signal and the known preamble over a window of v 38.

(57) samples. The window size depends on the preamble structure. Here, CP length is configured to be 1/4 of FFT length for simplicity. The delay correlation outputs ψ L and ψ R of the ith received samples can be written as v −1. ψ L ,n (i) = ∑ ( sL* ⋅ ri + ( n −1)⋅ f + k ) k =0. v −1. ψ R ,n (i ) = ∑ ( sR* ⋅ ri + ( n −1)⋅ f + k + v ) ,. (3.11). k =0. where sL and sR denote the {1,v} and {v+1,2×v} samples of the known short preamble respectively, v is equal to half of short preamble length, f equals short preamble length, and n equals 1, 2, 3, and 4. There are 8 delay correlation outputs will be stored in each received samples. In the following paragraphs, timing and frequency synchronization schemes which make use of the delay correlation outputs to achieve synchronization will be introduced. z. Timing synchronization: Timing synchronization involves finding the most significant path and the best possible time instant of the start of received data. After collecting groups of 8 delay correlation outputs obtained in Equation (3.11), the best timing instant can be detected by choosing the peak value of Ψ (i ) which is computed by z/2. z/2. Ψ (i ) = ∑ ψ R , n (i ) + ∑ ψ L , n (i ) , n =1. 2. 2. (3.12). n =1. where Ψ (i ) represents the timing acquisition metric, and z is the number of delay correlation outputs for the ith received samples and equals 8. Once the best starting position of the received signal is detected, frequency synchronization can then be performed. z. Frequency synchronization: Frequency synchronization deals with finding a wider range of the frequency offset between the transmitter and receiver local oscillators. The frequency offset estimation is developed by choosing the delay correlation 39.

(58) outputs that make a peak value of Ψ (i) . Hence a frequency offset estimate can be found based on the phase of the delay correlation outputs as follows: Δf = =. { }. 1 ∠ φdopt 2π T. (3.13). z / 2 −1 1 ⎧ z / 2−1 ⎫ ∠ ⎨ ∑ ψ L ,n (i )ψ L* ,n +1 (i ) + ∑ ψ R , n (i )ψ R* ,n +1 (i) ⎬ 2π T ⎩ n =1 n =1 ⎭. where T is the duration of the short preamble, dopt is the optimum timing acquisition instant, and z is the number of delay correlation outputs for the ith received samples. Although the residual frequency offset still exists, it can be estimated by using the pilot subcarriers embedded in the data symbols that will be introduced in Section 3.4. Computer simulations for the joint design of timing and frequency synchronization scheme are shown in Figures 3.3 and 3.4. First, Figure 3.3 shows the matched filter output of the proposed timing synchronization algorithm in a SISO-OFDM system. The simulation is carried out in the environment of ITU Vehicular B channel and simulated at Eb/N0 = 0 dB. As seen in Figure 3.3, the jointly designed algorithm with timing synchronization gives satisfactory result in the mobile and Rayleigh fading channel. The start of the received signal can be estimated directly by detecting the peak of the timing acquisition metric Ψ (i) .. 40.

(59) 3.5. x 10. 5. 3. 2.5. Match filter output. 2. 1.5. 1. 0.5. 0. 0. 5. 10. 15. 20. 25. 30. 35. Sample index. Figure 3.3: Matched filter output of the jointly designed algorithm for timing. synchronization under ITU Vehicular B channel model (at Eb/N0 = 0 dB). Figure 3.4 shows the MSE of the frequency offset estimate as a function of Eb/N0 in a SISO-OFDM system. SUI-3 channel model is used in this simulation. With the frequency offset estimation method, the average MSE is about 3 ×10−3 . For the scenario in which the oscillator offset is 20 kHz (about 10 ppm of the carrier frequency), the error of the frequency offset estimation method is just 60 Hz, which is much smaller than the subcarrier spacing. 0. 10. mean square error. -1. 10. -2. 10. -3. 10. -4. 10. 0. 5. 10. 15. 20. 25. Eb/No. Figure 3.4: MSE of the jointly designed algorithm for frequency synchronization under SUI-3 channel model 41.

(60) 3.3 Channel Estimation This section describes two channel estimation schemes to deal with different environments. After finding the packet starting point, channel estimation is performed to recover the channel frequency response. Preamble-aided channel estimation is suitable for static environment. However, pilot-aided channel estimation provides better performance than preamble-aided channel estimation in mobile environment. In the following we introduce the operations of two schemes [15], [16]. z. Preamble-aided channel estimation: Preamble-aided channel estimation is carried out by using the long preamble. Owing to the same symbol structure as data symbols, long preamble becomes the best candidate for performing this job. After removing CP, a receiver can perform channel estimation by taking FFT of the received long preamble to obtain the LS channel estimate H LP =. RLP FFT {lLP }. (3.14). where RLP is the received long preamble after taking FFT and lLP is the known long preamble. As shown in Figure 3.5, after taking FFT of received long preamble, we also require to transform the original long preamble into frequency domain. Thus, the channel frequency response can be obtained simply by dividing the FFT output of received long preamble and the FFT output of the original long preamble.. Time Domain Known. Long preamble (T) FFT. Unknown. *. Impulse response FFT. Long preamble (F). Frequency response. Known. Known. Known. Received LP (T) FFT. Received LP (F) Known. Frequency Domain. Figure 3.5: Preamble-aided channel estimation scheme 42.

(61) z. Pilot-aided channel estimation: Pilot-aided channel estimation is based on LS criteria together with channel interpolation based on piecewise-linear interpolation method. The pilot arrangement of WiMAX systems is comb-type pilot arrangement. The estimate of pilot signals in the sth OFDM symbol based on LS criterion is given by H Pilot , s = [ H Pilot , s (1) H Pilot ,s (2)...H Pilot , s ( N p )] = [. Rs ,1 Rs ,2 Ps ,1 Ps ,2. ". Rs , N p Ps , N p. ]. (3.15). where Ps ,l denotes the known N p pilot signals in the sth OFDM symbol and Rs ,l represents the pilot subcarriers in the sth received symbol after taking FFT, l = 1, 2, …, N p . After the estimation of the channel frequency response of pilot subcarriers, the channel response of data subcarriers can be interpolated according to adjacent pilot subcarriers. Piecewise-linear polynomial interpolation method is used here. Two successive pilot subcarriers are used to determine the channel response. in. between. the. pilot. subcarriers.. For. data. subcarrier. k,. ( j − 1) M < k ≤ jM , the estimated channel response is given by H int erp , s (k ) = H Pilot , s ( j ) +. m ( H Pilot , s ( j + 1) − H Pilot , s ( j )), 0 ≤ m < M M. (3.16). where M is the number of data subcarriers in between the adjacent pilot subcarriers and j = 1, 2, …, N p . The process of pilot-aided channel estimation is illustrated in Figure 3.6. H P ilot , s. Rs Received signals after FFT. Pilot subcarrier extraction. Pilot subcarrier channel estimation. Known pilot data. H in t erp , s Channel interpolation. Ps. Figure 3.6: Pilot-aided channel estimation scheme 43. Estimated channel frequency response.