Abstract
In this paper, we investigate the coexistence of two technologies that have been put forward for the fifth generation (5G) of cellular networks, namely, network-assisted device-to-device (D2D) communications and massive MIMO (multiple-input multiple-output). Potential benefits of both technologies are known individually, but the tradeoffs resulting from their coexistence have not been adequately addressed. To this end, we assume that D2D users reuse the downlink resources of cellular networks in an underlay fashion. In addition, multiple antennas at the BS are used in order to obtain precoding gains and simultaneously support multiple cellular users using multiuser or massive MIMO technique. Two metrics are considered, namely the average sum rate (ASR) and energy efficiency (EE). We derive tractable and directly computable expressions and study the tradeoffs between the ASR and EE as functions of the number of BS antennas, the number of cellular users and the density of D2D users within a given coverage area. Our results show that both the ASR and EE behave differently in scenarios with low and high density of D2D users, and that coexistence of underlay D2D communications and massive MIMO is mainly beneficial in low densities of D2D users.
Highlights
The research on future mobile broadband networks, referred to as the fifth generation (5G), has started in the past few years
Cellular user equipments (CUEs) should be a function of the number of base station (BS) antennas in order to benefit from massive MIMO in terms of the average sum rate (ASR) and EE
We considered a setup with uniformly distributed cellular users in the cell, while the D2D transmitters are distributed according to a Poisson point process
Summary
The research on future mobile broadband networks, referred to as the fifth generation (5G), has started in the past few years. Performance analysis: based on extensive simulations, we characterize the typical relation between the ASR and EE metrics in terms of the number of BS antennas, the number of CUEs, and the D2D user density for a given coverage area and study the incurred tradeoffs in two different scenarios. The coverage probability expression in Proposition 1 allows us to compute the average data rate of a typical D2D user in (10) The approximation in this proposition is due to neglecting the spatial interference correlation resulting from the fact that multiple interfering streams are coming from the same location (more details can be found in Appendix 1). Remark 7 The coverage probability of a typical CUE Pccov(βc) is a decreasing function of the D2D user density λd. In order to speed up the numerical computations, based on the insight obtained in Remark 6, we neglected the terms that are very small
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