Performance analysis of large scale MU-MIMO with optimal linear receivers

We consider the uplink of multicell multiuser MIMO (MU-MIMO) systems with very large antenna arrays at the base station (BS). We assume that the BS estimates the channel through uplink training, and then uses this channel estimate to detect the signals transmitted from a multiplicity of autonomous users in its cell. By taking the correlation between the channel estimate and the interference from other cells into account, we propose an optimal linear receiver (OLR) which maximizes the received signal-to-interference-plus-noise (SINR). Analytical approximations of the exact and lower bound on the achievable rate are then derived. The bound is very tight, especially at large number of BS antennas. We show that at low SINR, maximalratio combing (MRC) receiver performs as well as OLR, however at high SINR, OLR outperforms MRC. Compared with the typical minimum mean-square error receiver, our proposed OLR improves systematically the system performance, especially when the interference is large

Power Allocation Schemes for Multicell Massive MIMO Systems

This paper investigates the sum-rate gains brought by power allocation strategies in multicell massive multipleinput multiple-output systems, assuming time-division duplex transmission. For both uplink and downlink, we derive tractable expressions for the achievable rate with zero-forcing receivers and precoders respectively. To avoid high complexity joint optimization across the network, we propose a scheduling mechanism for power allocation, where in a single time slot, only cells that do not interfere with each other adjust their transmit powers. Based on this, corresponding transmit power allocation strategies are derived, aimed at maximizing the sum rate per-cell. These schemes are shown to bring considerable gains over equal power allocation for practical antenna configurations (e.g., up to a few hundred). However, with fixed number of users (N), these gains diminish as M turns to infinity, and equal power allocation becomes optimal. A different conclusion is drawn for the case where both M and N grow large together, in which case: (i) improved rates are achieved as M grows with fixed M/N ratio, and (ii) the relative gains over the equal power allocation diminish as M/N grows. Moreover, we also provide applicable values of M/N under an acceptable power allocation gain threshold, which can be used as to determine when the proposed power allocation schemes yield appreciable gains, and when they do not. From the network point of view, the proposed scheduling approach can achieve almost the same performance as the joint power allocation after one scheduling round, with much reduced complexity

Impact of User Mobility on Optimal Linear Receivers in Cellular Networks

We consider the uplink of non-cooperative multi-cellular systems deploying multiple antenna elements at the base stations (BS), covering both the cases of conventional and very large number of antennas. Given the inevitable pilot contamination and an arbitrary path-loss for each link, we address the impact of time variation of the channel due to the relative movement between users and BS antennas, which limits system's performance even if the number antennas is increased, as shown. In particular, we propose an optimal linear receiver (OLR) maximizing the received signal-to-interference-plus-noise (SINR). Closed-form lower and upper bounds are derived as well as the deterministic equivalent of the OLR is obtained. Numerical results reveal the outperformance of the proposed OLR against known linear receivers, mostly in environments with high interference and certain user mobility, as well as that massive MIMO is preferable even in time-varying channel conditions.Comment: 3 figures, 6 pages, accepted in ICC 201

Joint Optimization of Power Allocation and Training Duration for Uplink Multiuser MIMO Communications

In this paper, we consider a multiuser multiple-input multiple-output (MU-MIMO) communication system between a base station equipped with multiple antennas and multiple mobile users each equipped with a single antenna. The uplink scenario is considered. The uplink channels are acquired by the base station through a training phase. Two linear processing schemes are considered, namely maximum-ratio combining (MRC) and zero-forcing (ZF). We optimize the training period and optimal training energy under the average and peak power constraint so that an achievable sum rate is maximized.Comment: Submitted to WCN

On the Performance of MRC Receiver with Unknown Timing Mismatch-A Large Scale Analysis

There has been extensive research on large scale multi-user multiple-input multiple-output (MU-MIMO) systems recently. Researchers have shown that there are great opportunities in this area, however, there are many obstacles in the way to achieve full potential of using large number of receive antennas. One of the main issues, which will be investigated thoroughly in this paper, is timing asynchrony among signals of different users. Most of the works in the literature, assume that received signals are perfectly aligned which is not practical. We show that, neglecting the asynchrony can significantly degrade the performance of existing designs, particularly maximum ratio combining (MRC). We quantify the uplink achievable rates obtained by MRC receiver with perfect channel state information (CSI) and imperfect CSI while the system is impaired by unknown time delays among received signals. We then use these results to design new algorithms in order to alleviate the effects of timing mismatch. We also analyze the performance of introduced receiver design, which is called MRC-ZF, with perfect and imperfect CSI. For performing MRC-ZF, the only required information is the distribution of timing mismatch which circumvents the necessity of time delay acquisition or synchronization. To verify our analytical results, we present extensive simulation results which thoroughly investigate the performance of the traditional MRC receiver and the introduced MRC-ZF receiver