Adaptive Antenna Selection and Power Allocation in Downlink Massive MIMO Systems

Abstrak

Massive multi-input, multi-output (MIMO) systems are an exciting area of study and an important technique for fifth-generation (5G) wireless networks that support high data rate traffic. An increased number of antenna arrays at the base station (BS) consumes more power due to a higher number of radio frequency (RF) chains, which cannot be neglected and becomes a technical challenge. In this paper, we investigated how to obtain the maximal data rate by deriving the optimal number of RF chains from a large number of available antenna arrays at the BS when there is equal power allocation among users. Meanwhile, to mitigate inter-user-interference and to compute transmit power allocation, we used the precoding scheme zero forcing beamforming (ZFBF). The achievable data rate is increased because the algorithm of ZFBF enables the choosing of the maximum power in relation to the optimal antenna selection. We conclude that the transmit power allocation  allows the use of less number of RF chains which provides the maximum achievable data rate depending on the optimal RF chain at the BS.