Abstract

In a general wireless fading environment the multiple-input multiple-output (MIMO) system with an array of antennas both at the Basestation (BS) and user side helps in achieving high spectral density and reliable communication. For high density and huge data challenging network like 5G networks, massive MIMO replaces the conventional MIMO system. In massive MIMO, along with large number of users, a large array of antennas are used at the BS. So user scheduling along with appropriate antenna selection is a challenging task in such networks. In networks where low latency is a major requirement the process of scheduling of the users and selection of antenna should be of significantly low complexity. Here we discuss a very low complex scheme where both the user scheduling and antenna selection are performed simultaneously using the squared norm value of the channel matrix. This algorithm simultaneously generates a group of selected antennas from the BS and a group of scheduled user in an iterative fashion. From the initial set of selected BS antennas and the set of users, in each iteration the least favourable antenna and user are removed to finally produces a set of antennas and users which maximizes the sum-rate capacity of the system. The performance of the scheduling algorithm is compared with the Exhaustive search (ES) method. It is shown that the proposed scheme has the advantage over the the ES scheme in terms of very low computational complexity.

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