Effect of Different Permutation Scheme on Cumulative Distribu-

The different subchannel permutation scheme will affect SINR levels on each subchannel.

Fig. 5.19 shows three types of permutation scheme, adjacent permutation, adjacent permu-tation with multi-user scheduling (Band AMC) and distributed permupermu-tation scheme. By considering the outage threshold is 0 dB, Band AMC permutation will outperform than other permutation scheme because of muti-user diversity. However, the distributed per-mutation scheme is better than only adjacent perper-mutation scheme because of frequency

−150 −10 −5 0 5 10 15 20 25 0.1

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

SINR (dB)

CDF

Adjacent Permutation Band AMC Permutation Distributed Permutation

Figure 5.19: CDF of using different permutation schemes with 18 subcarriers are grouped a subchannel and under the symmetric traffic environment.

−300 −20 −10 0 10 20 30 40 0.1

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

SINR (dB)

CDF

Multi−carrier (18) Multi−carrier (9) Multi−carrier (4) Multi−carrier (2) Single−carrier (1)

Figure 5.20: CDF of using different number of subcarrier are grouped a subchannel with distributed permutation scheme under the symmetric traffic environment.

diversity. Hence, we can use different permutation scheme in different environment. In general, the adjacent Band AMC subcarrier permutations can be properly used for fixed or low mobility environments because it can select higher channel gain of MS on each sub-channel. The distributed subcarrier permutation perform very well in mobile applications because the channel state information can’t be estimated very well. However, different number of subcarriers are grouped a subchannel also affect the frequency diversity gain on distributed permutation scheme. Fig. 5.20 shows five different numbers of subcarrier are grouped a subchannel. We can realize more numbers are grouped can improve outage probability, but less resource units can be used in system. For the single carrier case, the outage probability is almost 0.4 that is higher than link requirement. We can select multi-carrier case, such as multi-multi-carrier (18). Then, the outage probability is improved to 0.15 since we can use less resource units to exchange higher link quality. These kinds of options enable the system designers to trade number of served MS for higher link quality in the TDD-OFDMA system.

5.5 Conclusions

In this chapter, we employee traditional frequency reuse scheme and FFR scheme in a TDD-OFDMA multi-cellular system for supporting asymmetric services. As the simu-lation results show, we suitably use FFR scheme by designing the inner radius and each region reuse factor that can maximize system throughput with guaranteeing link reliability.

We can find out FFR scheme is more suitable used in random asymmetric traffic environ-ments and is effectively mitigate strong cross-slot interference that is caused in random asymmetric traffic environments. In addition, if system want to maintain link reliability, it must use some spectrum to exchange higher link reliability. Hence, using FFR scheme in an asymmetric environment can provide better link quality and increase system throughput by adaptively revising each design factors.

80

CHAPTER 6

Conclusions and Future Research

6.1 Outage Performance Analysis for FFR TDD-OFDMA Systems with Asymmetric Traffics: Two Cell Case

In Chapter 4, we have analyzed the relationship of CTS and size of inner region of FFR scheme by the queueing theorem in a two-cells TDD-OFDMA system. We present an analytical formula that can evaluate the link successful probability for a FFR based on TDD-OFDMA system by using regular subchannels assignment. We provide the different CTS to show how to effect the successful probability and how to design the size of inner region. As the simulation results shown, the analytical approach can effectively help design the inner region size of FFR system and adaptively changing the size of inner region to guaranty the successful probability in the multi-cellular environment with various ratios of the uplink to downlink traffic among cells.

6.2 Outage Performance Analysis for FFR TDD-OFDMA Systems with Asymmetric Traffics: Multi-Cellular Case

In Chapter 5, we have developed a GUI interface to help us investigate FFR scheme in a TDD-OFDMA multi-cellular system for supporting asymmetric services. We can use the

interface to observe different system performance under different random asymmetric traf-fic environments. As the simulation show, FFR scheme is more suitable to implement in a random asymmetric traffic environment than traditional frequency reuse scheme and liter-ature work that using time slot strategy to avoid cross-slot interference. The FFR scheme can maintain link reliability by adjust inner region radius and outer region reuse factor.

In a random asymmetric traffic environment, interference management is more important than spectrum efficiency because of the strong cross-slot interference. Thus, we must use lower usage ratios of spectrum to exchange higher link reliability. Hence, we propose FFR scheme that be implemented TDD-OFDMA system to solve the effects of cell inter-ference adaptively especially system can support random asymmetric traffic environments.

6.3 Future Research

For the future research of the thesis, we provide the following suggestions to extend our work:

• Power control can be considered in each transmission mode and region even considering soft frequency reuse scheme.

• Consider the different traffic load situation and see how to effect design factors of FFR scheme.

• Different subchannels assignment in frame duration and find out the optimal subchan-nels assignment in multi-celluar system with supporting asymmetric.

82

Bibliography

[1] WiMAX Forum. (2008, Jul. 7) WiMAX System Evaluation Methodology v2.1.

[Online]. Available: www.wimaxforum.org

[2] 3GPP. (2008, May) Evolved Universal Terrestrial Radio Access (E-UTRA): Physical channels and modulation (release 8).

[3] T. S. KO-06.0082/R1. (2005, Dec.) Specifications for 2.3GHz Band Portable Internet Service: Physical and Medium Access Control Layer.

[4] C.-J. Chen and L.-C. Wang, “Suppressing Opposite-Direction Interference in TDD/CDMA Systems with Asymmetric Traffic by Antenna Beamforming,” IEEE Transactions on Vehicular Technology, vol. 53, pp. 956–967, July 2004.

[5] L.-C. Wang, S.-Y. Huang, and Y.-C. Tseng, “Interference Analysis and Resource Al-location for TDD-CDMA Systems to Support Asymmetric Services by Using Direc-tional Antennas,” IEEE Transactions on Vehicular Technology, vol. 54, pp. 1056–

1069, May 2005.

[6] S.-H. Wie and D.-H. Cho, “Time Slot Allocation Scheme Based on a Region Division in CDMA/TDD Systems,” in Proc. IEEE Vehicular Technology Conference (VTC’01-Spring), May 2001.

[7] Y. S. Choi, I. Sohn, and K. B. Lee, “A Novel Decentralized Time Slot Allocation Algorithm in Dynamic TDD System,” in Proc. IEEE Consumer Communications and Networking Conference (CCNC’06), Jan. 2006.

[8] I. Sohn, Y. S. Choi, and K. B. Lee, “Comparison of Decentralized Time Slot Al-location for Asymmetric Traffic in TDD Systems,” IEEE Transactions on Wireless Communications, vol. 8, pp. 2990–3003, June 2009.

[9] H.-J. Chung, M.-R. Kim, N.-M. Kim, and S. Yun, “Time Slot Allocation Based on Region and Time Partitioning for Dynamic TDD-OFDM Systems,” in Proc. IEEE Vehicular Technology Conference (VTC’06-Spring), May 2006.

[10] W. Jeong and M. Kavehrad, “Cochannel Interference Reduction in Dynamic-TDD Fixed Wireless Applications, Using Time Slot Allocation Algorithms,” IEEE Trans-actions on Communications, vol. 50, pp. 1627–1636, Oct. 2002.

[11] J. Nasreddine and X. Lagrange, “Time Slot Allocation Based on a Path Gain Division Scheme for TD-CDMA TDD Systems,” in Proc. IEEE Vehicular Technology Confer-ence (VTC’03-Spring), Apr. 2003.

[12] E. Foutekova, P. Agyapong, and H. Haas, “Channel Asymmetry in Cellular OFDMA-TDD Networks,” EURASIP Journal on Wireless Communication and Networking, Oct. 2008.

[13] H. Lee and D.-H. Cho, “Combination of Dynamic-TDD and Static-TDD Based on Adaptive Power Control,” in Proc. IEEE Vehicular Technology Conference (VTC’08-Fall), Sept. 2008.

[14] M. Assaad, “Optimal Fractional Frequency Reuse (FFR) in Multi-Cellular OFDMA System,” in Proc. IEEE Vehicular Technology Conference (VTC’08-Fall), Sept. 2008.

[15] N.U.L. Hassan and M. Assaad, “Optimal Fractional Frequency Reuse (FFR) and Re-source Allocation in Multiuser OFDMA System,” in Proc. International Conference on Information and Communication Technologies (ICICT’09), Aug. 2009.

[16] R. Giuliano, C. Monti, and P. Loreti, “WiMAX Fractional Frequency Reuse for Rural Environment,” IEEE Wireless Communications, vol. 15, pp. 60–65, June 2008.

[17] H. Fujii and H. Yoshino, “Theoretical Capacity and Outage Rate of OFDMA Cellu-lar System with Fractional Frequency Reuse,” in Proc. IEEE VehicuCellu-lar Technology Conference (VTC’08-Spring), May 2008.

[18] H. Lei, L. Zhang, and X. Zhang, “A Novel Multi-cell OFDMA System Structure Using Fractional Frequency Reuse,” in Proc. IEEE International Symposium on Per-sonal, Indoor and Mobile Radio Communications (PIMRC’07), Sept. 2007.

[19] R. Y. Chang, Z. Tao, J. Zhang, and C.-C. J. Kuo, “A Graph Approach to Dynamic Fractional Frequency Reuse (FFR) in Multi-Cell OFDMA Networks,” in Proc. IEEE International Conference on Communications (ICC’09), 2009.

[20] F. Khan, LTE for 4G Mobile Broadband. Cambridge University Press, 2009.

[21] S. Mehrotra, “On the Implementation of a Primal-Dual Interior Point Method,” SIAM Journal on Optimization, vol. 2, pp. 575–601, Nov. 1992.

[22] J. G. Andrews, A. Ghosh, and R. Muhamed, Fundamentals of WiMAX. Prentice-Hall, 2007.

[23] J. P. Linnartz, Narrowband Land-Mobile Radio Networks, Boston, MA: Artech House, 1993.

[24] C. F. Ball, E. Humburg, K. Ivanov, and R. MLullner, “Rapid Estimation Method for Data Capacity and Spectrum Efficiency in Cellular Networks,” in Proc. IST Mobile and Wireless Communication Summit, June 2005.

[25] Donald Gross, John F. Shortle, and Carl M. Harris, Fundamentals of Queueing The-ory, 4th ed. Wiley, 2008.

[26] D. G. Jeong and W. S. Jeon, “CDMA/TDD System for Wireless Multimedia Services with Traffic Unbalance Between Uplink and Downlink,” IEEE Journal on Selected Areas in Communications, vol. 17, pp. 939–946, May 1999.

[27] W. S. Jwon and D. G. Jeong, “Call Admission Control for Mobile Multimedia Com-munications with Traffic Asymmetry Between Uplink and Downlink,” IEEE Trans-actions on Vehicular Technology, vol. 50, pp. 59–66, Jan. 2001.

[28] D. Bertsekas and R. Gllager, Data Networks, 2nd ed. Prentice-Hall, 1992.

[29] Simulating the SUI Channel Models, IEEE 802.16 Working Group, IEEE 802.16.3c-01/53, April. 2001.

Vita

Wei-Chi Liwas born in Taiwan, R. O. C. in 1986. He received a B.S. in Electronic and Engineering from Chang Gaung University of Technology in 2008. From July 2008 to September 2010, he worked his Master degree in the Wireless Systems Lab in the De-partment of Communication Engineering at National Chiao-Tung University. His research interests are in the field of wireless communications.