基于高斯混合模型的下行小区间干扰分布

严小军; 徐景; 朱元萍; 杨旸; 王江

doi:10.11999/JEIT151459

基于高斯混合模型的下行小区间干扰分布

doi: 10.11999/JEIT151459

基金项目:

国家自然科学基金(61571303)，国家科技部国际合作项目(2014DFE10160)，国家重大专项(2015ZX03002004)，上海市科委项目(15511103200)

计量
- 文章访问数: 1345
- HTML全文浏览量: 135
- PDF下载量: 396
- 被引次数: 0
出版历程
- 收稿日期: 2015-12-24
- 修回日期: 2016-05-19
- 刊出日期: 2016-10-19

Distribution of Downlink Inter-cell Interference Based on Gaussian Mixture Model

Funds:

The National Natural Science Foundation of China (61571303), The International Science and Technology Cooperation Program of China (2014DFE10160), The National Science and Technology Major Project (2015ZX03002004), The Science and Technology Commission of Shanghai Municipality (15511103200)

摘要

摘要: 在正交频分多址接入(Orthogonal Frequency Division Multiple Access, OFDMA)蜂窝网络中，小区间干扰的统计特性与网络性能密切相关。下行小区间干扰的累积分布函数(Cumulative Distribution Function, CDF)还没有一个闭合表达式。该文提出一种参数可显式计算的高斯混合模型对下行小区间干扰分布进行近似。进一步，利用高斯混合模型将下行小区间干扰的累积分布函数近似表示为若干个误差函数的加权和。仿真验证了高斯混合模型的准确性，并且表明基于高斯混合模型的累积分布函数能很好地近似下行小区间干扰的累积分布函数。
- 无线通信 /
- 正交频分多址接入 /
- 小区间干扰 /
- 高斯混合模型 /
- 累积分布函数
Abstract: In Orthogonal Frequency Division Multiple Access (OFDMA)-based cellular networks, the statistical characteristics of the Inter-Cell Interference (ICI) are closely related to network performances. There is no closed-form expression for the Cumulative Distribution Function (CDF) of the ICI. The Gaussian Mixture Model (GMM) whose parameters can be computed explicitly is proposed to approximate the distribution of the downlink ICI. Then using the GMM, the CDF of the ICI is approximated as the weighted sum of some error functions. Simulation verifies the accuracy of the GMM and shows that the CDF based on the GMM can well approximate the CDF of the ICI.
- Wireless communications /
- Orthogonal Frequency Division Multiple Access (OFDMA) /
- Inter-cell interference /
- Gaussian Mixture Model (GMM) /
- Cumulative Distribution Function (CDF)

HTML全文

参考文献(25)

ELSAWY H, HOSSAIN E, and HAENGGI M. Stochastic geometry for modeling, analysis, and design of multi-tier and cognitive cellular wireless networks: A survey[J]. IEEE Communications Surveys Tutorials, 2013, 15(3): 996-1019. doi: 10.1109/SURV.2013.052213.00000.

GONG Zhenhua and HAENGGI M. Interference and outage in mobile random networks: Expectation, distribution, and correlation[J]. IEEE Transactions on Mobile Computing, 2014, 13(2): 337-349. doi: 10.1109/TMC.2012.253.

MORAITIS N and PANAGOPOULOS A D. Multiple airborne radio interference to cellular networks: Statistical modeling approach[J]. IEEE Aerospace and Electronic Systems Magazine, 2013, 28(11): 21-27. doi: 10.1109/MAES. 2013.6678489.

MOONTAHA S, AKTER F, RAHMAN F, et al. BER performance of DS-CDMA system over a multipath Rayleigh fading channel considering path gain component and noise variance[C]. Proceedings of the IEEE International Conference on Electrical Engineering and Information Communication Technology, Dhaka, 2015: 1-5.

ANDREWS J G, BUZZI S, CHOI W, et al. What will 5G be[J]. IEEE Journal on Selected Areas in Communications, 2014, 32(6): 1065-1082. doi: 10.1109/JSAC.2014.2328098.

CHEN Shanzhi and ZHAO Jian. The requirements, challenges, and technologies for 5G of terrestrial mobile telecommunication[J]. IEEE Communications Magazine, 2014, 52(5): 36-43. doi: 10.1109/MCOM.2014.6815891.

HOSSAIN E, RASTI M, TABASSUM H, et al. Evolution toward 5G multi-tier cellular wireless networks: An interference management perspective[J]. IEEE Wireless Communications, 2014, 21(3): 118-127. doi: 10.1109/MWC. 2014.6845056.

FENTON L F. The sum of log-normal probability distributions in scatter transmission systems[J]. IRE Transactions on Communications Systems, 1960, 8(1): 57-67. doi: 10.1109/TCOM.1960.1097606.

BEAULIEU N C and XIE Qiong. An optimal lognormal approximation to lognormal sum distributions[J]. IEEE Transactions on Vehicular Technology, 2004, 53(2): 479-489. doi: 10.1109/TVT.2004.823494.

MEHTA N, WU Jingxian, MOLISCH A, et al. Approximating a sum of random variables with a lognormal [J]. IEEE Transactions on Wireless Communications, 2007, 6(7): 2690-2699. doi: 10.1109/TWC.2007.051000.

SUNG K W, HAAS H, and MCLAUGHLIN S. A semi- analytical PDF of downlink SINR for femtocell networks[J]. EURASIP Journal on Wireless Communications and Networking, 2010, 2010(5): 1-9. doi: 10.1155/2010/256370.

LAM C and LE-NGOC T. Log-shifted gamma approximation to lognormal sum distributions[J]. IEEE Transactions on Vehicular Technology, 2007, 56(4): 2121-2129. doi: 10.1109/ TVT.2007.897662.

NIE Hong and CHEN Shaohua. Lognormal sum approximation with type IV Pearson distribution[J]. IEEE Communications Letters, 2007, 11(10): 790-792. doi: 10.1109/LCOMM.2007.070842.

ZHANG Qitu and SONG S H. A systematic procedure for accurately approximating lognormal-sum distributions[J]. IEEE Transactions on Vehicular Technology, 2008, 57(1): 663-666. doi: 10.1109/TVT.2007.905611.

RENZO M D, GRAZIOSI F, and SANTUCCI F. Further results on the approximation of log-normal power sum via Pearson type IV distribution: a general formula for log-moments computation[J]. IEEE Transactions on Communications, 2009, 57(4): 893-898. doi: 10.1109/ TCOMM.2009.04.070133.

YANG Jun and WANG Ning. A simple Pearson distribution based detector with applications to time-hopping multiuser UWB receiver design[C]. Proceedings of the IEEE Wireless Communications and Networking Conference, Shanghai, 2013: 2591-2596.

LI Xue, WU Zhijin, CHAKRAVARTHY V, et al. A low- complexity approximation to lognormal sum distributions via transformed log skew normal distribution[J]. IEEE Transactions on Vehicular Technology, 2011, 60(8): 4040-4045. doi: 10.1109/TVT.2011.2163652.

PATEFIELD M and TANDY D. Fast and accurate calculation of Owens t function[J]. Journal of Statistical Software, 2000, 5(5): 1-25. doi: 10.18637/jss.v005.i05.

3GPP TR 36.814-2010. Evolved universal terrestrial radio access(EUTRA); further advancements for E-UTRA physical layer aspects[S]. 2010.

ETSI TR 125 996-2010. Universal mobile telecommunications system (UMTS); spacial channel model for multiple input multiple output (MIMO) simulations[S]. 2010.

ABRAMOWITZ M and STEGUN I A. Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables[M]. New York: Dover, 1972: 923-924.

HYVRINEN A, KARHUNEN J, and OJA E. Independent Component Analysis[M]. New York: John Wiley Sons, 2001: 36-43.

ZHANG Tiankui, AN Lu, and CHEN Yue. Aggregate interference statistical modeling and user outage analysis of heterogeneous cellular networks[C]. Proceedings of the IEEE International Conference on Communications, Sydney, 2014: 1260-1265.

COVER T M and THOMAS J A. Elements of Information Theory[M]. New York: John Wiley Sons, 2006: 19-20.

ABU-DAYYA A and BEAULIEU N C. Outage probabilities in the presence of correlated lognormal interferers[J]. IEEE Transactions on Vehicular Technology, 1994, 43(1): 164-173. doi: 10.1109/25.282277.

施引文献

资源附件(0)

访问统计