The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced pr...The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced procedure of Multiple-Input Multiple-Output, which improves the performance of Wireless Local Area Networks. Moreover, Multi-user Multiple-Input Multiple-Output leads the Wireless Local Area Networks toward covering more areas. Due to the growth of the number of clients and requirements, researchers try to improve the performance of the Medium Access Control protocol of Multi-user Multiple-Input Multiple-Output technology to serve the user better, by supporting different data sizes, and reducing the waiting time to be able to transmit data quickly. In this paper, we propose a Clustering Multi-user Multiple-Input Multiple-Output protocol, which is an improved Medium Access Control protocol for Multi-user Multiple-Input Multiple-Out-put based on MIMOMate clustering technique and Padovan Backoff Algorithm. Utilizing MIMOMMate focuses on the signal power which only serves the user in that cluster, minimizes the energy consumption and increases the capacity. The implementation of Clustering Multi-user Multiple-Input Multiple-Output performs on the Network Simulator (NS2.34) platform. The results show that Clustering Multi-user Multiple-Input Multiple-Output protocol improves the throughput by 89.8%, and reduces the latency of wireless communication by 43.9% in scenarios with contention. As a result, the overall performances of the network are improved.展开更多
For reducing the inter-user interference in multi-user multiple-input multiple-output（MU-MIMO） wireless communication systems,e.g.,MIMO-orthogonal frequency division multiplexing（MIMO-OFDM） systems,it is often des...For reducing the inter-user interference in multi-user multiple-input multiple-output（MU-MIMO） wireless communication systems,e.g.,MIMO-orthogonal frequency division multiplexing（MIMO-OFDM） systems,it is often desirable to the complex preprocessing at the transmitter.This paper proposes a multi-user beamforming algorithm with sub-codebook selection.Based on the minimal leakage criterion,the codebook selection,limited feed-forward and minimum mean square error（MMSE） detection are combined in the proposed algorithm.This avoids the complex channel matrix decomposition and inversion.Consequently,the computational complexity at the transmitter is significantly reduced.Simulation results show that the proposed algorithm performs better than existing beamforming algorithms.展开更多
近年来,多用户多输入多输出(Multiple-User Multiple-Input Multiple-Output,MU-MIMO)下行链路的预编码算法设计吸引了越来越多研究者的兴趣。然而目前并没有对基站端已知信道误差概率分布且约束条件为单天线功率约束(Per-Antenna Power...近年来,多用户多输入多输出(Multiple-User Multiple-Input Multiple-Output,MU-MIMO)下行链路的预编码算法设计吸引了越来越多研究者的兴趣。然而目前并没有对基站端已知信道误差概率分布且约束条件为单天线功率约束(Per-Antenna Power Constraints,PAPCS)的情况下的线性预编码算法的研究。针对上述情况,以遍历和速率(Expected Sum Rate)最大化为优化准则,主要基于约束随机逐次凸近似(Constrained Stochastic Successive Convex Approximation,CSSCA)、二阶对偶法、交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)及高斯随机化(Gaussian Randomization)设计了线性预编码算法。所提算法的适用场景更符合实际情况,而且实验仿真结果证明,算法的性能较好。展开更多
针对在多用户多输入多输出(multi-user multiple input multiple output,MU-MIMO)系统中,选择性映射(selected mapping,SLM)算法不适用于分布式用户,并且边信息无法在用户之间共享的问题,提出一种适用于MU-MIMO系统的广义SLM算法。该算...针对在多用户多输入多输出(multi-user multiple input multiple output,MU-MIMO)系统中,选择性映射(selected mapping,SLM)算法不适用于分布式用户,并且边信息无法在用户之间共享的问题,提出一种适用于MU-MIMO系统的广义SLM算法。该算法通过改变相位旋转的作用对象,将相位旋转进行前置,来解决SLM引入带来的一系列问题。同时,分析了在采用等增益传输波束成形的系统中,使用广义SLM算法时系统的高峰均功率比(peak to average power ratio,PAPR)性能,验证了该算法的有效性。仿真结果也表明了该算法可以有效降低MU-MIMO系统的PAPR。展开更多
文摘The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced procedure of Multiple-Input Multiple-Output, which improves the performance of Wireless Local Area Networks. Moreover, Multi-user Multiple-Input Multiple-Output leads the Wireless Local Area Networks toward covering more areas. Due to the growth of the number of clients and requirements, researchers try to improve the performance of the Medium Access Control protocol of Multi-user Multiple-Input Multiple-Output technology to serve the user better, by supporting different data sizes, and reducing the waiting time to be able to transmit data quickly. In this paper, we propose a Clustering Multi-user Multiple-Input Multiple-Output protocol, which is an improved Medium Access Control protocol for Multi-user Multiple-Input Multiple-Out-put based on MIMOMate clustering technique and Padovan Backoff Algorithm. Utilizing MIMOMMate focuses on the signal power which only serves the user in that cluster, minimizes the energy consumption and increases the capacity. The implementation of Clustering Multi-user Multiple-Input Multiple-Output performs on the Network Simulator (NS2.34) platform. The results show that Clustering Multi-user Multiple-Input Multiple-Output protocol improves the throughput by 89.8%, and reduces the latency of wireless communication by 43.9% in scenarios with contention. As a result, the overall performances of the network are improved.
基金support by the National Natural Science Foundation of China (60702060)the 111 Project
文摘For reducing the inter-user interference in multi-user multiple-input multiple-output（MU-MIMO） wireless communication systems,e.g.,MIMO-orthogonal frequency division multiplexing（MIMO-OFDM） systems,it is often desirable to the complex preprocessing at the transmitter.This paper proposes a multi-user beamforming algorithm with sub-codebook selection.Based on the minimal leakage criterion,the codebook selection,limited feed-forward and minimum mean square error（MMSE） detection are combined in the proposed algorithm.This avoids the complex channel matrix decomposition and inversion.Consequently,the computational complexity at the transmitter is significantly reduced.Simulation results show that the proposed algorithm performs better than existing beamforming algorithms.
文摘近年来,多用户多输入多输出(Multiple-User Multiple-Input Multiple-Output,MU-MIMO)下行链路的预编码算法设计吸引了越来越多研究者的兴趣。然而目前并没有对基站端已知信道误差概率分布且约束条件为单天线功率约束(Per-Antenna Power Constraints,PAPCS)的情况下的线性预编码算法的研究。针对上述情况,以遍历和速率(Expected Sum Rate)最大化为优化准则,主要基于约束随机逐次凸近似(Constrained Stochastic Successive Convex Approximation,CSSCA)、二阶对偶法、交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)及高斯随机化(Gaussian Randomization)设计了线性预编码算法。所提算法的适用场景更符合实际情况,而且实验仿真结果证明,算法的性能较好。
文摘针对在多用户多输入多输出(multi-user multiple input multiple output,MU-MIMO)系统中,选择性映射(selected mapping,SLM)算法不适用于分布式用户,并且边信息无法在用户之间共享的问题,提出一种适用于MU-MIMO系统的广义SLM算法。该算法通过改变相位旋转的作用对象,将相位旋转进行前置,来解决SLM引入带来的一系列问题。同时,分析了在采用等增益传输波束成形的系统中,使用广义SLM算法时系统的高峰均功率比(peak to average power ratio,PAPR)性能,验证了该算法的有效性。仿真结果也表明了该算法可以有效降低MU-MIMO系统的PAPR。
