Vector Precoding Design Based on Nested-lattice-coding for MU-MIMO Relay Systems
-
摘要: 针对多输入多输出(MIMO)中继多用户系统的多址传输问题，为了提高系统可达速率和误码率性能，该文利用嵌套晶格码具有可达加性高斯白噪声信道容量的特性，设计一种基站和中继联合预编码的方法。基站端的嵌套晶格码结合矢量扰动(VP)预编码，以控制发送信号的功率。由于矢量扰动预编码和嵌套晶格码都存在相同的模运算步骤，因此在中继端的模运算抑制噪声功率的同时消除了冗余矢量。接着实现中继联合迫整数预编码方法，这种基站/中继混合预编码技术能够控制等效噪声功率，实现对蜂窝用户的有效信号传输。更进一步地，在给出整系数矩阵和扰动矢量矩阵的计算方法后，以最大化系统可达速率为目标对基站和中继的功率实现最优分配。实验结果表明，该方案在可达速率和误码性能方面优于现有方案。Abstract: This paper focused on the problem of the multi-access transmission in multiuser Multiple-Input Multiple-Output (MIMO) relay systems. In order to improve the performance in terms of system capacity and bit error rate, a joint precoding approach for the base station and the relay station is proposed by exploiting nested lattice coding which is capable of achieving modulo-channel capacity with additive Gaussian noise. At base station, the nested lattice coding is equipped up with Vector Perturbation (VP) precoding, leading to a reduction in transmit power. Since the modulo operation with respect to VP precoding is identical to that in nested coding, the relay can not only depress the noise power but also remove the redundant information with one-step modulo operation. An integer-forcing precoding method is designed for the relay to reduce the equivalent noise. Moreover, the acquisition of both the integral coefficient matrix and the vector perturbation matrix is provided. The transmit power allocation between the base station and the relay is optimized to maximize the system sum rate. The outstanding performance of the proposed scheme is validated by the simulation results.
-
[1] BASHAR F and ABOUTORAB N. Outage probability of spatially diverse multi-source multi-relay multi-user two-hop relay networks[C]. IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020: 1–6. [2] 李高祥, 杨霖, 林旭彬. 基于能量收集的多对双向MIMO AF中继系统的和速率分析[J]. 电子学报, 2019, 47(3): 531–537. doi: 10.3969/j.issn.0372-2112.2019.03.003LI Gaoxiang, YANG Lin, and LIN Xubin. Sum rate analysis of multi-pair two-way MIMO AF relay system based on energy harvesting[J]. Acta Electronica Sinica, 2019, 47(3): 531–537. doi: 10.3969/j.issn.0372-2112.2019.03.003 [3] 王进, 束锋, 尤肖虎, 等. 基于OFDM多用户对双向中继宽带无线网络空频信道配对与功率分配[J]. 中国科学:信息科学, 2015, 45(7): 878–888. doi: 10.1360/N112014-00280WANG Jin, SHU Feng, YOU Xiaohu, et al. Space-frequency channel pairing and power allocation for OFDM-based multi-pair two-way relay wireless networks[J]. Scientia Sinica Informationis, 2015, 45(7): 878–888. doi: 10.1360/N112014-00280 [4] 王毅, 林艳, 黄永明, 等. 基于成对用户大规模MIMO两跳中继系统的最优能效设计[J]. 电子与信息学报, 2017, 39(1): 1–8. doi: 10.11999/JEIT160245WANG Yi, LIN Yan, HUANG Yongming, et al. Optimal energy-efficient design for two-hop massive MIMO relaying systems with multi-pair users[J]. Journal of Electronics &Information Technology, 2017, 39(1): 1–8. doi: 10.11999/JEIT160245 [5] VENTURELLI R B and SILVA D. Optimization of integer-forcing precoding for multi-user MIMO downlink[J]. IEEE Wireless Communications Letters, 2020, 9(11): 1860–1864. doi: 10.1109/LWC.2020.3006393 [6] 雷维嘉, 周洋, 谢显中, 等. MIMO全双工双向安全通信系统的预编码矩阵设计[J]. 通信学报, 2020, 41(10): 156–171. doi: 10.11959/j.issn.1000-436x.2020155LEI Weijia, ZHOU Yang, XIE Xianzhong, et al. Design of precoding matrices in MIMO full duplex two-way security communication system[J]. Journal on Communications, 2020, 41(10): 156–171. doi: 10.11959/j.issn.1000-436x.2020155 [7] JIANG Hua, CHENG Hao, SHEN Lizhen, et al. Joint lattice-reduction-aided precoder design for multiuser MIMO relay system[J]. KSII Transactions on Internet and Information Systems, 2016, 10(7): 3010–3025. doi: 10.3837/tiis.2016.07.008 [8] GOPAL L, RONG Yue, and ZANG Zhuquan. Joint MMSE transceiver design in non-regenerative MIMO relay systems with covariance feedback[C]. The 17th Asia-Pacific Conference on Communications, Kota Kinabalu, Malaysia, 2011: 290–294. [9] CAI Yunlong, DE LAMARE R C, YANG Lieliang, et al. Robust MMSE precoding based on switched relaying and side information for multiuser MIMO relay systems[J]. IEEE Transactions on Vehicular Technology, 2015, 64(12): 5677–5687. doi: 10.1109/TVT.2014.2383388 [10] PHUYAL U, JHA S C, and BHARGAVA V K. Joint zero-forcing based precoder design for QoS-aware power allocation in MIMO cooperative cellular network[J]. IEEE Journal on Selected Areas in Communications, 2012, 30(2): 350–358. doi: 10.1109/JSAC.2012.120214 [11] CHAE C B, TANG Taiwen, HEATH R W, et al. MIMO relaying with linear processing for multiuser transmission in fixed relay networks[J]. IEEE Transactions on Signal Processing, 2008, 56(2): 727–738. doi: 10.1109/TSP.2007.907821 [12] LIU Ling, YAN Yanfei, LING Cong, et al. Construction of capacity-achieving lattice codes: Polar lattices[J]. IEEE Transactions on Communications, 2019, 67(2): 915–928. doi: 10.1109/TCOMM.2018.2876113 [13] KURKOSKI B M. Encoding and indexing of lattice codes[J]. IEEE Transactions on Information Theory, 2018, 64(9): 6320–6332. doi: 10.1109/TIT.2018.2839181 [14] NAZER B and GASTPAR M. Compute-and-forward: Harnessing interference through structured codes[J]. IEEE Transactions on Information Theory, 2011, 57(10): 6463–6486. doi: 10.1109/TIT.2011.2165816 [15] LIM S H, FENG Chen, PASTORE A, et al. Compute-forward for DMCs: Simultaneous decoding of multiple combinations[J]. IEEE Transactions on Information Theory, 2020, 66(10): 6242–6255. doi: 10.1109/TIT.2020.3009634 [16] CHENG Hai, YUAN Xiaojun, and TAN Yihua. Generalized compute-compress-and-forward[J]. IEEE Transactions on Information Theory, 2019, 65(1): 462–481. doi: 10.1109/TIT.2018.2864638 [17] TAN Yihua and YUAN Xiaojun. Compute-compress-and-forward: Exploiting asymmetry of wireless relay networks[J]. IEEE Transactions on Signal Processing, 2016, 64(2): 511–524. doi: 10.1109/TSP.2015.2481876 [18] HUANG Y C, NARAYANAN K R, and WANG P C. Lattices over algebraic integers with an application to compute-and-forward[J]. IEEE Transactions on Information Theory, 2018, 64(10): 6863–6877. doi: 10.1109/TIT.2018.2848277 [19] SILVA D, PIVARO G, FRAIDENRAICH G, et al. On integer-forcing precoding for the Gaussian MIMO broadcast channel[J]. IEEE Transactions on Wireless Communications, 2017, 16(7): 4476–4488. doi: 10.1109/TWC.2017.2699178 [20] GAN Y H, LING Cong, and MOW W H. Complex lattice reduction algorithm for low-complexity full-diversity MIMO detection[J]. IEEE Transactions on Signal Processing, 2009, 57(7): 2701–2710. doi: 10.1109/TSP.2009.2016267 [21] SAHRAEI S and GASTPAR M. Polynomially solvable instances of the shortest and closest vector problems with applications to compute-and-forward[J]. IEEE Transactions on Information Theory, 2017, 63(12): 7780–7792. doi: 10.1109/TIT.2017.2759281 [22] WEN Jinming, ZHOU Baojian, MOW W H, et al. Compute-and-forward protocol design based on improved sphere decoding[C]. IEEE International Conference on Communications (ICC), London, UK, 2015: 1631–1636. [23] SAKZAD A, HARSHAN J, and VITERBO E. Integer-forcing MIMO linear receivers based on lattice reduction[J]. IEEE Transactions on Wireless Communications, 2013, 12(10): 4905–4915. doi: 10.1109/TWC.2013.090513.121465 [24] BOYD S and VANDENBERGHE L. Convex Optimization[M]. Cambridge: Cambridge University Press, 2004. -
下载:
图(6)
计量
- 文章访问数: 514
- HTML全文浏览量: 276
- PDF下载量: 72
- 被引次数: 0
下载:
