4 Diversity Reception and Phase Noise Compensation in
4.3 Phase Noise Compensation
4.3.5 Determination of Sample Size
In the following, according to the theoretical analysis, we will discuss the determination of sample size in the case of the batch processing technique for ICI and noise compensation applied in both the time- and frequency-domains. The RMS delay spread of a Rayleigh fading channel in a DVB-T system is given by
2 finger. The corresponding coherence bandwidth is given by
1 157.62 (KHz)
c 5
rms
B ≈ τ = (4.19)
The tone spacing in a DVB-T system of 8 MHz bandwidth is 3.9625 KHz such that there are about 40 tones within the coherence bandwidth. When the batch processing scheme is used in the frequency domain, the optimal sample size is obtained based on the coherence bandwidth in (4.19). In addition, the coherence time will be derived in terms of velocity (Doppler frequency). The Doppler frequency for a moving terminal with velocity v is given by
UHF d
f v f
≈ c (4.20)
where fUHF and c are the carrier frequency in UHF band and light speed, respectively.
The coherence time can be expressed as 9
c 16
d
T ≈ π f (4.21)
When we exploit batch processing in the time domain, the optimal sample size can be chosen based on the coherence time in (4.21). Suppose the velocity is 5 m/s for example. The corresponding Doppler frequency f is about 7.9 Hz such that the d coherence time is about 22700 μs. Since the duration of an OFDM symbol in DVB-T systems is 280μs, there are about 81 OFDM symbols within the coherence time.
4.4 Computer Simulations
In this section, computer simulations are conducted to evaluate the BER performance of DVB-T systems. Throughout the simulations, we only deal with the discrete time signal processing of the baseband; hence pulse-shaping and matched-filtering are removed for simplicity. In addition, timing synchronization is assumed to be perfect. All channel parameters are listed in Table 3.6. Unless otherwise mentioned, the following parameters are assumed: phase noise variance = 0.1 and mobile velocity v = 5 m/s. In the first simulation, the efficacy of the phase noise compensation scheme using batch processing in the time domain is evaluated with the sample size varied. The BER performances as a function of input SNR Eb/N0 shown in Figs. 4.18(a)-(c) for phase noise variance = 0.4, 0.1, and 0.04, respectively, indicate that the system performances are degraded as the phase noise variance increases. It is observed that the algorithm with too smaller or larger sample size leads to worse performance. This is because that the smaller sample size cannot completely compensate the phase noise effect due to lack of enough sampled data. On the other hand, in the case of larger sample size, the variation of channel will destroy the assumption of fixed channel condition during the processing time and then fail to successfully collect the desired signals, leading to performance degradation. It is noteworthy that in this simulation, the optimal performance can be achieved by the optimal sample size Nb equaling to 34.
In the second simulation, the efficacy of the phase noise compensation scheme with batch processing in the frequency domain is examined with the sample size varied.
The BER performances shown in Figs. 4.19(a)-(c) corresponding to Figs. 4.18(a)-(c), respectively, follow the same trend as observed in the time domain processing, except that the optimal sample size Nb equals to 24 which is smaller than that obtained in Fig.
4.18. In addition, the frequency domain processing exhibits significant performance degradation as compared to the time domain method. This is because sample size within the coherence time is larger than that within the coherence bandwidth as long as channel variation is not obvious.
In the third simulation, the efficacy of the phase noise compensation scheme with batch processing in the time-frequency domain is investigated with the sample size
varied. The BER performances shown in Figs. 4.20 for the phase noise variance = 0.1 follow the same trend as observed in Fig. 4.18(b), except that the time-frequency domain processing outperforms both the time and frequency domain processing.
In the fourth simulation, the fading effect on the phase noise compensation schemes with batch processing in the time domain is investigated with mobile velocity v = 20 m/s and the sample size varied. The result shown in Fig. 4.21 indicates that the performance is worse than that of mobile velocity v = 5 m/s in Fig. 4.18 due to the severe fading. Furthermore, the optimal sample size of Nb =16 is smaller than that obtained in Fig. 4.18(b), which is Nb =34. This is because channel response may change severely in time dimension when the mobile velocity is fast; hence larger sample size will significant degrade the system performance.
In the final simulation, a comparison among the conventional MRC, and the phase noise compensation schemes with batch processing in the time, frequency, and time-frequency domains is investigated with the sample size varied. In this simulation, the optimal sample sizes and ( are used for batch processing in the time, frequency, and time-frequency domain, respectively. The BER performances shown in Fig. 4.22 indicate that the batch processing in the time-frequency domain outperforms the other methods. This is because channel variation in time-frequency processing is much slower, leading to successful suppression of phase noise and significant performance enhancement.
34, 24
Nb = 8,16)
4.5 Summary
In this chapter, we first review the diversity reception schemes including MRC, SBSD, CDD, MRC with CDD, IVSD, PVSD, and PBSD. The corresponding performance and computational complexity are then investigated. Among them, the selection between the selective and combining diversity schemes is based on the trade-off between BER performance and computational complexity. In addition, in order to improve the performance degradation due to phase noise, we propose the decision feedback phase noise compensation scheme incorporating batch processing in the time, frequency, or time-frequency domain. The proposed receiver is shown to outperform the conventional MRC method and enhance robustness against phase noise.
Diversity combining or selection Diversity combining or selection
Outer
FFTFFT Demod.Demod.
Channel
Diversity combining or selection Diversity combining or selection
Outer
FFTFFT Demod.Demod.
Channel
Diversity combining or selection Diversity combining or selection
Outer
FFTFFT Demod.Demod.
Channel
Figure 4.1: Various diversity reception schemes at different stages in DVB-T system.
1st stage: symbol-based selective diversity (SBSD) and cyclic delay diversity (CDD).
2nd stage: MRC and MRC with CDD.
3rd stage: in-Viterbi selective diversity (IVSD).
4th stage: post-Viterbi selective diversity (PVSD).
5th stage: packet-based selective diversity (PBSD).
δ
M-1δ
M-1IFFTIFFT IFFT
Tx
δ
1δ
1δ
M-1δ
M-1IFFTIFFT IFFT
Tx
δ
1δ
1Figure 4.2: OFDM system with delay diversity at transmitter side.
(a) (b)
Figure 4.3: Effect of DD over a typical indoor channel. (a) Without DD. (b) With DD.
IFFTIFFT
Figure 4.4: OFDM system with phase diversity at transmitter side.
FFTFFT
Figure 4.5: Equivalent model of transmitter and the receiver with CDD in OFDM system.
FFTFFT
MRCMRC
FFTFFT
Channel estimation
Channel estimation
Channel estimation
Channel estimation Cyclic
delay Cyclic Cyclic delay delay
FFTFFT
MRCMRC
FFTFFT
Channel estimation
Channel estimation
Channel estimation
Channel estimation Cyclic
delay Cyclic Cyclic delay delay
Figure 4.6: MRC with CDD at receiver side in OFDM system.
Figure 4.7: BER performances of CDD and MRC in DVB-T systems with cyclic delay varied as a parameter.
QPSK constellation
Figure 4.8: Illustration of symbol location induced by random noise under QPSK constellation.
one survivor from the four paths
one survivor from the four paths
path metric path select
Figure 4.9: Illustration of diversity reception scheme with IVSD.
Equal to path memory length Equal to path memory length
Figure 4.10: Different branches selected and compared after passing through a long path after Viterbi decoding.
Figure 4.11: BER performances of different diversity reception schemes in DVB-T system.
Figure 4.12: BER performance of MRC and PBSD decoder with outer channel coding in DVB-T system.
Figure 4.13: 16QAM signals without compensating CPE effect induced by phase noise in frequency domain.
FFTFFT
Demod.. ViterbiViterbiViterbi
Mod.Mod.
Demod.. ViterbiViterbiViterbi
Mod.Mod.
Figure 4.14: Illustration of decision feedback phase noise compensator with batch processing in DVB-T system.
time
freq.
time
freq.
Figure 4.15: Phase noise compensation using batch processing for collection of OFDM symbols in time domain.
time
freq.
time
freq.
Figure 4.16: Phase noise compensation using batch processing for collection of data tones in frequency domain.
time
freq.
time
freq.
Figure 4.17: Phase noise compensation using batch processing for collection of OFDM symbols and data tones in time-frequency domain.
(a)
(b)
(c)
Figure 4.18: BER performances obtained by using phase noise compensation in time domain with sample size varied and velocity v = 5 m/s. (a) Phase noise variance = 0.4. (b) Phase noise variance = 0.1. (c) Phase noise variance
= 0.04.
(a)
(b)
(c)
Figure 4.19: BER performances obtained by using phase noise compensation in frequency domain with sample size varied and velocity v = 5 m/s. (a) Phase noise variance = 0.4. (b) Phase noise variance = 0.1. (c) Phase noise variance = 0.04.
Figure 4.20: BER performances obtained by using phase noise compensation in time-frequency domain with sample size varied, velocity v = 5 m/s and phase noise variance = 0.1.
Figure 4.21: BER performances obtained by using phase noise compensation in time domain with sample size varied, velocity v = 20 m/s and phase noise variance = 0.1.
Figure 4.22: BER performances obtained by using conditional MRC and phase noise compensation in time, frequency, and time-frequency domain with velocity v = 5 m/s and phase noise variance = 0.1.
Chapter 5 Conclusion
In this thesis, we propose a DVB-T system incorporating diversity reception and phase noise compensation schemes. With the aid of diversity reception algorithms, we show that the receiver can achieve better link performance and provide robustness against fading effects due to multipath. On the other hand, the phase noise compensator can successfully combat the phase noise introduced by the imperfect oscillators at the transmitter and receiver sides. In Chapter 2, some key concepts of the receive diversity techniques have been introduced; the effects of phase noise and Doppler shift in an OFDM system are also studied. Furthermore, with diversity scheme used, a receiver with enhanced system performance is presented for suppression of phase noise and ICI.
In Chapter 3, based on the DVB-T technical specification, we construct a simulation platform of a DVB system using Matlab and ADS software tools used.
Synchronization and channel estimation algorithms for a DVB-T receiver are also investigated. In particular, we present two feasible synchronization schemes: One is cyclic-prefix-based synchronization, which enables self-synchronization in an OFDM system. Self-synchronization is an idea to exploit the duplication characteristic of cyclic prefix in OFDM symbols. The other one is pilot-based synchronization using a pilot-correlation detector to extract the synchronization information at the pilot tones from the received signal. With regards to channel estimation, the LS channel estimation with linear interpolation and the lowpass filtering in the transform domain are included for refining estimation of the channel response, in which the LS-based channel estimation is aimed to be implemented with lower complexity while the other is
targeted at better performance.
In Chapter 4, the diversity reception and phase noise compensation algorithms are presented. We first review the diversity reception schemes including MRC, SBSD, CDD, MRC with CDD, IVSD, PVSD, and PBSD. The corresponding performance and computational complexity are then investigated. Among them, the selection between the selective and combining diversity schemes is based on the trade-off between BER performance and computational complexity. In order to combat phase noise, we propose the decision feedback phase noise compensation scheme incorporating batch processing in the time, frequency, or time-frequency domain. It is shown that the proposed scheme outperforms the conventional MRC method and enhances robustness against phase noise.
The study presented in the thesis has thoroughly discussed the receiver design for a DVB-T system and its efficacy has been rigorously verified using the simulation platform. In particular, we deliver feasible solutions to advanced DTV systems. In practice, there are yet several other limitations remaining to be considered in implementing a DVB-T system, such as memory usage, operating speed, and gate counts. For the sake of fast development and low cost, the development platform should adopt a programmable prototyping communication system including the existing functions presented in the thesis. Furthermore, a similar specification, referred to as DVB-handheld (DVB-H), is regarded as an extension to DVB-T standard.
DVB-H is envisioned as a "one-to-many" broadcast project, enabling the distribution of music, film clips or other multimedia contents to a large audience via mobile handsets.
A critical issue in DVB-H is power consumption. In conclusion, developing a compliant hardware platform for DVB-T and detailed algorithms for DVB-H will be a challenge in the future.
Bibliography
[1] J. Rinne, “Some elementary suboptimal diversity reception schemes for DVB-T in mobile conditions,” Consumer Electronics, IEEE Transactions on, Vol. 46, No. 3, pp. 847-850, Aug. 2000.
[2] S. Kaiser, “Spatial transmit diversity techniques for broadband OFDM systems,”
GLOBECOM '00, IEEE, Vol. 3, pp. 1824-1828, Nov.-Dec. 2000.
[3] K. Witrisal, Y. H. Kim, R. Prasad, and L. P. Ligthart, “Antenna diversity for OFDM using cyclic delays,” SCVT’01, Benelu, pp. 13-17, Oct. 2001.
[4] M. Bossert, A. Huebner, F. Schuehlein H. Haas, and E. Costa, “On cyclic delay diversity in OFDM based transmission schemes,” InOWo’02, Hamburg, 5 pages on CD-Rom, Sep. 2002.
[5] A. Dammann and S. Kaiser, “Standard conformable antenna diversity techniques for OFDM and its application to the DVB-T system,” GLOBECOM '01, IEEE, Vol.
5, pp. 3100-3105, Nov. 2001.
[6] T. Sakai, K. Kobayashi, S. Kubota, M. Morikura, and S. Kato, “Soft-decision Viterbi decoding with diversity combining,” GLOBECOM '90. IEEE, Vol. 2, pp.
1127-1131, Dec. 1990.
[7] T. Sakai, K. Kobayashi, S. Kubota, M. Morikura, and S. Kato, “Soft-decision Viterbi decoding with diversity combining for multi-beam mobile satellite communication systems,” Selected Areas in Communications, IEEE Journal on, Vol. 13, No. 2, pp. 285-290, Feb. 1995.
[8] T. Onizawa, M. Mizoguchi, T. Sakata, and M. Morikura “A new simple adaptive phase tracking scheme employing phase noise estimation for OFDM signals,”
VTC’02, IEEE, Vol. 3, pp. 1252-1256, May 2002.
[9] L. Piazzo, and P. Mandarini “Analysis of phase noise effects in OFDM modems,”
Communications, IEEE Transactions on, Vol. 50, No. 10, pp. 1696-1705, Oct.
2002.
[10] H. G.. Ryu, and Y. S. Lee “Phase noise analysis of the OFDM communication system by the standard frequency deviation,” Consumer Electronics, IEEE Transactions on, Vol. 49, No. 1, pp. 41-47, Feb. 2003.
[11] V. Simon, A. Senst, M. Speth, and H. Meyr “Phase noise estimation via adapted interpolation,” GLOBECOM '01. IEEE, Vol. 6, pp. 3297-3301, Nov. 2001.
[12] B. Stantchev and G. Fettweis “Time-variant distortions in OFDM,”
Communications, IEEE Letters on, Vol. 4, No. 10, pp. 312-314, Oct. 2000.
[13] M. S. El-Tanany, Y. Wu, and L. Házy, “Amalytical modeling and simulation of phase noise interference in OFDM-based digital television terrestrial broadcasting systems,” Broadcasting, IEEE Transactions on, Vol. 47, No. 1, Mar. 2001.
[14] A. García Armada, “Understanding the effects of phase noise in orthogonal frequency division multiplexing (OFDM),” Broadcasting, IEEE Transactions on, Vol. 47, No. 2, pp. 153-159, Jun. 2001.
[15] P. Robertson and S. Kaiser, “Analysis of the effects of phase-noise in orthogonal frequency division multiplexing (OFDM) systems,” ICC’95, Seattle, Jun. 1995.
[16] K. Nikitopoulos and A. Polydoros, “Joint channel equalization and residual frequency offset and phase noise compensation in OFDM systems,” InOWo’02, Hamburg, Sep. 2002.
[17] K. Nikitopoulos and A. Polydoros, “Analysis of new and existing methods of reducing intercarrier inyerference due to carrier frequency offset in OFDM,”
Communications, IEEE Transactions on, Vol. 47, No. 3, Mar. 1999.
[18] K. Nikitopoulos and A. Polydoros, “Compensation schemes for phase noise and residual frequency offset in OFDM systems,” GLOBECOM '01. IEEE, Vol.1, pp.
330-333, Nov. 2001.
[19] A. García Armada and M. Calvo, “Phase noise and sub-carrier spacing effects on the performance of an communication system,” Communications, IEEE Letters on, Vol. 2, No. 1, pp. 11-13, Jan. 1998.
[20] R. Narasimhan, “Performance of diversity schemes for OFDM systems with frequency offset, phase noise and channel estimation errors,” ICC’02. IEEE, Vol. 3, pp. 1551-1557, Apr.-May 2002.
[21] R. Narasimhan, “Performance of diversity schemes for OFDM systems with frequency offset, phase noise and channel estimation errors,” Communications, IEEE Transactions on, Vol. 50, No. 10, Oct. 2002.
[22] J. Shentu, K. Panta, and J. Armstrong, “Effects of phase noise on performance of OFDM systems using an ICI cancellation scheme” Broadcasting, IEEE Transactions on, Vol. 49, No. 2, Jun. 2003.
[23] ETSI, Digital video broadcasting (DVB), “Framing structure, channel coding and modulation for digital terrestrial television,” EN 300 744 v1.4.1, Jan. 2001.
[24] M. Massel, “Digital television DVB-T COFDM and ATSC 8-VSB,”
Digitaltvbooks.Com, Oct. 2000.
[25] T. S. Rappaport, “Wireless Communications: Principles and Practice,” Prentice Hall, 1999.
[26] Y. Zhao and S.-G. Häggman, “Sensitivity to Doppler shift and carrier frequency errors in OFDM systems – The consequences and solutions,” VTC’96, IEEE, Vol.
3, pp. 1564-1568, April-May 1996.
[27] R. van Nee and R. Prasad, “OFDM for Wireless Multimedia Communications,”
Artech House, 2000.
[28] J. Terry and J. Heiskala, ”OFDM Wireless LANs: A Theoretical and Practical Guide,” Sams, 2001.
[29] D. Liu, C. Wei, and C. Chang, “An extension of guard-interval based symbol and frequency synchronization technique for wireless OFDM transmission,” VTC’01.
IEEE, Vol. 4, pp. 2324-2328, Oct. 2001.
[30] F. Classen and H. Meyr, “Frequency synchronization algorithms for OFDM systems suitable for communication over frequency selective fading channels,”
VTC’94, IEEE, Vol. 3, pp. 1655-1653, Jun. 1994.
[31] M. Hsieh and C. Wei, ”A low-complexity frame synchronization and frequency offset compensation scheme for OFDM systems over fading channels,” Vehicular Technology, IEEE Transactions on, Vol. 48, No. 5, pp. 1596-1609, 1999.
[32] M. Hsieh and C. Wei, “Channel estimation for OFDM systems based on comb-type pilot arrangement in frequency selective fading channels,” Consumer Electronics, IEEE Transactions on, Vol. 44, No. 1, pp. 217-225, Feb. 1998.
[33] Y. Zhao and A. Huang, “A novel channel estimation method for OFDM mobile communication systems based on pilot signals and transform-domain processing,”
VTC’97, IEEE, Vol. 3, pp. 2089-2093, May 1997.
[34] E. Al-Susa, “A predictor-based decision feedback channel estimation method for COFDM with high resilience to rapid time-variations,” VTC’97, IEEE, pp.
273-278, May 1997.