User association and load balancing for cellular massive MIMO

Abstract

Abstract-Massive MIMO is expected to play a key role in coping with the predicted mobile-data traffic explosion. Indeed, in combination with small cells and TDD operation, it promises large throughputs per unit area with low latency. In this paper we focus on the problem of balancing the load across networks with massive MIMO base-stations (BSs). The need for load balancing arises from variations in the user population density and is more pronounced in small cells due to the large variability in coverage area. We consider methods for load balancing over networks with small and large massive MIMO BSs. As we show, the distinct operation and properties of massive MIMO enable practical resource-efficient load-balancing methods with nearoptimal performance.

User association in massive MIMO and mmWave enabled HetNets powered by renewable energy

“…The primal variable X can be recovered by substituting the optimal dual variables into (13). We note that due to the discrete nature of the primal problem in (9), solving dual problem may not be the same as solving the primal problem. Nevertheless, the optimal solution of the dual problem always leads to good primal solutions [20].…”

“…Recent research efforts have been devoted to examine the UA for load balancing in massive MIMO cellular networks [9] and mmWave wireless networks [10]. In [9], small and large massive MIMO BSs were deployed in the cellular networks and max-rate based and load based associations were analyzed.…”

“…In [9], small and large massive MIMO BSs were deployed in the cellular networks and max-rate based and load based associations were analyzed. In [10], the problem of UA in a 60-GHz wireless network was considered, and a resource allocation solution was proposed to guarantee the balance and fairness of the system.…”

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“…This is an approach that has been pursued in cellular heterogeneous networks [14], [16], with the rationale that a well-chosen network-utility function can reflect some fairness criterion. Specifically, UE j receives a utility U j (R j ) when its data rate is R j .…”

Distributed resource allocation in virtualized wireless cellular networks based on ADMM

“…In this paper, we adopt the wellknown logarithmic function u(x) = log x, x > 0 to our utility function. The logarithmic function has been widely used in where utility estimation is calculation [11]. Another constraint that represents the data rate allocated by SP i to user k i is given by…”