Large-Scale MIMO Versus Network MIMO for Multicell Interference Mitigation

Abstract

Abstract-This paper compares two important downlink multicell interference mitigation techniques, namely, large-scale (LS) multiple-input multiple-output (MIMO) and network MIMO. We consider a cooperative wireless cellular system operating in timedivision duplex (TDD) mode, wherein each cooperating cluster includes B base-stations (BSs), each equipped with multiple antennas and scheduling K single-antenna users. In an LS-MIMO system, each BS employs BM antennas not only to serve its scheduled users, but also to null out interference caused to the other users within the cooperating cluster using zero-forcing (ZF) beamforming. In a network MIMO system, each BS is equipped with only M antennas, but interference cancellation is realized by data and channel state information exchange over the backhaul links and joint downlink transmission using ZF beamforming. Both systems are able to completely eliminate intra-cluster interference and to provide the same number of spatial degrees of freedom per user. Assuming the uplink-downlink channel reciprocity provided by TDD, both systems are subject to identical channel acquisition overhead during the uplink pilot transmission stage. Further, the available sum power at each cluster is fixed and assumed to be equally distributed across the downlink beams in both systems. Building upon the channel distribution functions and using tools from stochastic ordering, this paper shows, however, that from a performance point of view, users experience better quality of service, averaged over small-scale fading, under an LS-MIMO system than a network MIMO system. Numerical simulations for a multicell network reveal that this conclusion also holds true with regularized ZF beamforming scheme. Hence, given the likely lower cost of adding excess number of antennas at each BS, LS-MIMO could be the preferred route toward interference mitigation in cellular networks.

Optimizing large-scale MIMO cellular downlink: Multiplexing, diversity, or interference nulling?

“…1 and 2 plot the per-BS ergodic sum rate of an LS-MIMO system with M = 15 for various combinations of (K, ζ, O) obtained numerically via simulations and analytically using (2). As the results show, when a substantial number of dimensions are devoted to nulling interference (large O), the numerical and analytic results are in good agreement.…”

“…It is nearly optimum for each BS to operate independently of the other BSs and not to spend spatial resources on nulling interference. More specifically, the sum-rate optimal operating point obtained numerically is (K * , ζ * , O * ) = (8,6,2), and the optimal operating point obtained analytically is (K * , ζ * , O * ) = (10, 6, 0). The difference between the achievable sum rates at these two operating points (obtained numerically) is only about 4%.…”

“…Having a large number of base-station (BS) antennas at our disposal allows us to achieve multiple system objectives simultaneously: (1) serve multiple users in the same time-frequency slot to achieve a multiplexing gain, (2) provide diversity for the scheduled users, and (3) as often stated as a major advantage of massive MIMO systems, null interference at out-of-cell users. In fact, in the limit as the number of antennas goes to infinity, intercell interference can be completely eliminated, leaving pilot contamination as the only limiting factor [1].…”

“…In fact, in the limit as the number of antennas goes to infinity, intercell interference can be completely eliminated, leaving pilot contamination as the only limiting factor [1]. This paper focuses on the design of large-scale MIMO (LS-MIMO) downlink systems [2], where each BS is equipped with a large but finite number of antennas. In this regime, it is crucial to understand the tradeoffs between multiplexing, diversity and interference nulling.…”

Massive MIMO Wireless Networks: An Overview

“…[13]. Both systems mitigate interferences of multi cellular wireless networks in separate ways and are not to be confused with each other [14]. Networked MIMO emulates distributed antenna arrays by creating clusters of connected BSs.…”