基于格基约减的扩频通信多址干扰抑制算法

鲍亚川; 蔚保国

doi:10.11999/JEIT161104

基于格基约减的扩频通信多址干扰抑制算法

doi: 10.11999/JEIT161104

鲍亚川¹,
蔚保国¹

基金项目:

国家自然科学基金(91638203)，国家重点研发计划(2016YFB0502102)

计量
- 文章访问数: 986
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- 被引次数: 0
出版历程
- 收稿日期: 2016-10-18
- 修回日期: 2017-03-06
- 刊出日期: 2017-05-19

Lattice Reduction Aided Multiple Access Interference Cancellation Algorithm of Spread Spectrum Communication

BAO Yachuan¹,
YU Baoguo¹

Funds:

The National Natural Science Foundation of China (91638203), The National Key Research and Development Program (2016YFB0502102)

摘要

摘要: 在链路资源受限条件下的扩频通信应用中，多址干扰是限制系统多用户服务能力和通信质量的主要因素。该文针对多址干扰消除问题，首次将格基约减理论应用到扩频通信多址干扰消除中，提出基于格基约减辅助的多用户检测算法，通过格基约减变换实现对信号间互相关矩阵的正交性优化，使多用户检测算法性能得到改进，以较低的运算复杂度实现了逼近最大似然算法的检测性能。该算法在对抗强远近效应方面表现出优异性能，不同于传统多用户检测算法在恶劣多址环境下检测性能的严重退化，该算法能够保持对最大似然检测算法性能的逼近，可以使扩频通信系统的传输可靠性、多用户服务能力以及环境适应性得到显著增强。
- 扩频通信 /
- 多址干扰 /
- 多用户检测 /
- 格基约减 /
- 远近效应
Abstract: In the application of spread spectrum communication with limited wireless resource, Multiple Access Interference (MAI) is the main restraint element of the multiple user service capability and communication performance. Focusing on the MAI problem, lattice reduction theory is firstly applied to the MAI cancellation of spread spectrum communication. A lattice reduction aided multiple user detection method is proposed. With lattice reduction method, the orthogonality of the correlation matrix of multiple signals is improved. As a result, the error bit rate of Multiple User Detection (MUD) method is reduced, and near ML demodulation performance is reached with low complexity. High performance on near-far effect resistance is achieved with the algorithm. Contrary to the performance degradation of traditional MUD method in serious MAI scenario, lattice reduction aided multiple user detection method can maintain near ML performance. Transmission reliability, multiuser service capability and environment suitability of spread spectrum system can be improved remarkably with the algorithm.
- Spread spectrum communication /
- Multiple access interference /
- Multiple user detection /
- Lattice reduction /
- Near-far effect

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参考文献(18)

ABDELAAL R, ELSAYED K F, and ISMAIL M. Optimized joint power and resource allocation for coordinated multi-point transmission for multi-user LTE-Advanced systems[J]. Wireless Personal Communications, 2015, 83(4): 1-22. doi: 10.1007/s11277-015-2543-7.

BOTELLA C, ERO G, and DIEGO M. Multi-user interference mitigation under limited feedback requirements for WCDMA systems with base station cooperation[J]. Telecommunication Systems, 2016, 61(3): 543-557. doi: 10.1007/s11235-015-0011-z.

HOU Y, LI M, and YUAN X. Cooperative interference mitigation for heterogeneous Multi-Hop wireless networks coexistence[J]. IEEE Transactions on Wireless Communications, 2016, 15(8): 5328-5340. doi: 10.1109/TWC. 2016.2555953.

ZHOU Qi and MA Xiaoli. Receiver designs for differential UWB systems with multiple access interference[J]. IEEE Transactions on Communications, 2014, 62(1): 126-134. doi: 10.1109/ICUWB.2011.6058828.

ARNAU J, DEVILLERS B, MOSQUERA C, et al. Performance study of multiuser interference mitigation schemes for hybrid broadband multibeam satellite architectures[J]. EURASIP Journal on Wireless Communications Networking, 2012: 132. doi: 10.1186/ 1687-1499-2012-132.

KECHRIOTIES G I and MANOLAKOS E S. Hopfield neural network implementation of the optimal CDMA multiuser detector[J]. IEEE Transactions on Communications, 1996, 44(4): 496-507. doi: 10.1109/72.478397.

史双宁, 尚勇, 梁庆林. 一种新的线性多用户检测器[J]. 电子学报, 2007, 35(3): 426-429. doi: 10.3321/j.issn:0372-2112. 2007.03.008.

SHI Shuangning, SHANG Yong, and LIANG Qinglin. A novel linear multi-user detector[J]. Acta Electronica Sinica, 2007, 35(3): 426-429. doi: 10.3321/j.issn:0372-2112.2007.03.008.

YU Y, LI J, and WANG Z. Blind multiuser detection in MC-CDMA: Schmidt-orthogonalization and subspace tracking kalman filtering[C]. 3rd International Conference on Communications and Mobile Computing, Qingdao, 2011: 375-380. doi: 10.1109/CMC.2011.50.

XIE Z, SHORT R T, and RUSHFORTH C K. A family of suboptimum detectors for coherent multiuser communications[J]. IEEE Journal on Selected Areas in Communications, 1990, 8(4): 683-690. doi: 10.1109/49.54464.

ZHENG W, LI J, LUO Y, et al. Multi-user interference pre-cancellation for downlink signals of multi-beam satellite system[C]. International Conference on Consumer Electronics, Communications and Networks, Xianning, 2013: 415-418. doi: 10.1109/CECNet.2013.6703358.

BAO Yachuan and YU Baoguo. A MAI cancellation algorithm with near ML performance[C]. 2015 IEEE International Conference on Communication Software and Networks (ICCSN), Chengdu, 2015: 196-200. doi: 10.1109/ ICCSN.2015.7296153.

BREMNER M R. Lattice Basis Reduction: An Introduction to the LLL Algorithm and Its Applications[M]. Boca Raton, FL, USA, CRC Press, Inc., 2011: 55-62.

DIAS S M and VIEIRA N J. Concept lattices reduction: Definition, analysis and classification[J]. Expert Systems with Applications, 2015, 42(20): 7084-7097. doi: 10.1016/j.eswa. 2015.04.044.

LAMACCHIA B A. Basis reduction algorithms and subset sum problems[D]. [Master dissertation], Massachusetts Inst Technology, 1991.

LENSTRA A K, LENSTRA H W, and LOVASZ L. Factoring polynomials with rational coefficients[J]. Mathematische Annalen, 1982, 261(4): 515-534. doi: 10.1007/BF01457454.

NGUYEN P Q and STERN J. Lattice reduction in cryptology: An update[C]. 4th International Symposium on Algorithmic Number Theory, Netherlands, 2000: 85-112. doi: 10.1007/10722028_4.

SCHNORR C and EUCHNER M. Lattice basis reduction: Improved practical algorithms and solving subset sum problems[J]. Mathematical Programming, 2006, 66(1-3): 68-85. doi: 10.1007/bf01581144.

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