This paper provides an analytical performance characterization of both uplink (UL) and downlink (DL) user-centric network multiple-input multiple-output (MIMO) systems, where a cooperating BS cluster is formed for each user individually and the clusters for different users may overlap. In this model, cooperating BSs (each equipped with multiple antennas) jointly perform zero-forcing beamforming to the set of single-antenna users associated with them. As compared to a baseline network MIMO systems with disjoint BS clusters, the effect of user-centric clustering is that it improves signal strength in both UL and DL, while reducing cluster-edge interference in DL. This paper quantifies these effects by assuming that BSs and users form Poisson point processes and by further approximating both the signal and interference powers using Gamma distributions of appropriate parameters. We show that BS cooperation provides significant gain as compared to single-cell processing for both UL and DL, but the advantage of user-centric clustering over the baseline disjoint clustering system is significant for the DL cluster-edge users only. Although the analytic results are derived with the assumption of perfect channel state information and infinite backhaul between the cooperating BSs, they nevertheless provide architectural insight into the design of future cooperative cellular networks. A. Related WorkNetwork MIMO has long been advocated as being capable of treating inter-cell interference as useful signals, thereby significantly improving the throughput of wireless cellular networks [2], [3]. But the existing performance evaluation of network MIMO systems has been mostly carried out either using simplified Wyner model or by simulation; and most earlier works have focused on the optimization of transmit strategies for network MIMO systems. For example, for network MIMO systems with disjoint clustering, earlier work [4] numerically studies the throughput performance; [5], [6] present optimization strategies where users close to cluster edge are served 2 with inter-cluster coordination and users close to cluster center are served only with intra-cluster BS coordination. Likewise for user-centric clustering, first proposed in [7], most existing works are based on numerical investigation and optimization strategies that select the best serving cluster of BSs for each user [8], [9], [10].The performance analysis of network MIMO systems is a challenging task, because the cooperating BSs in a network MIMO system typically have different path-loss to the user, so traditional analytic tools for MIMO system, such as the random matrix theory [11], are not ideally suited for analyzing the network MIMO system performance, unless certain symmetry and simplifying assumptions are adopted [12].To account for the distance dependent path-loss in wireless communication networks, stochastic geometry has emerged as a powerful tool for analyzing wireless networks with random deployment of BSs and users that are assumed to form Poisson point processe...
A base-station (BS) equipped with multiple antennas can use its spatial dimensions in three different ways: (1) to serve multiple users, thereby achieving a multiplexing gain, (2) to provide spatial diversity in order to improve user rates and (3) to null interference in neighboring cells. This paper answers the following question: What is the optimal balance between these three competing benefits? We answer this question in the context of the downlink of a cellular network, where multi-antenna BSs serve multiple single-antenna users using zero-forcing beamforming with equal power assignment, while nulling interference at a subset of out-of-cell users. Any remaining spatial dimensions provide transmit diversity for the scheduled users. Utilizing tools from stochastic geometry, we show that, surprisingly, to maximize the per-BS ergodic sum rate, with an optimal allocation of spatial resources, interference nulling does not provide a tangible benefit. The strategy of avoiding inter-cell interference nulling, reserving some fraction of spatial resources for multiplexing and using the rest to provide diversity, is already close-to-optimal in terms of the sum-rate. However, interference nulling does bring significant benefit to cell-edge users, particularly when adopting a rangeadaptive nulling strategy where the size of the cooperating BS cluster is increased for cell-edge users.
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