Sum-Rate Performance of Massive MIMO Systems in Highly Scattering Channel with Semi-Orthogonal and Random User Selection


Дәйексөз келтіру

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Аннотация

The sum-rate performance of a massive MIMO system is dependent on the adequate user and antenna selection techniques. It is best when all the selected users are mutually orthogonal (MOU) and antennas are selected based on maximum channel gain. In the case, when number of antennas in massive MIMO is approximately hundreds, the computational complexity cost in joint user and antenna selection is very high. Semi-orthogonal user selection (SUS) is preferred to reduce interference and complexity cost. In highly scattering Rayleigh fading channel random user selection (RUS) technique can be used because of small loss of system sum-rate compared toSUSandMOUtechniques. In this paper we propose a joint user and antenna selection algorithm where users are scheduled using semi-orthogonality measure and antenna selection is based on maximum channel gain. In addition, an algorithm for joint user and antenna selection is reported here with RUS for user selection and maximum channel gain for antenna selection. We explore the system sum-rate performance of a massive MIMO system using these algorithms for the case of a highly scattering Rayleigh fading channel. We consider various precoding techniques MMSE, ZFBF, and MRT and a range of SNR. We also explore the effect of spatial and multiuser diversity on system sum-rates using proposed algorithms. The sum-rate obtained by algorithms-1 is greater than the algorithm-2 about 1–3% but second one is much simpler.

Авторлар туралы

Tasher Sheikh

North Eastern Regional Institute of Science and Technology

Хат алмасуға жауапты Автор.
Email: tasher372@gmail.com
Үндістан, Arunachal Pradesh

Joyatri Bora

North Eastern Regional Institute of Science and Technology

Email: tasher372@gmail.com
Үндістан, Arunachal Pradesh

Md. Hussain

North Eastern Regional Institute of Science and Technology

Email: tasher372@gmail.com
Үндістан, Arunachal Pradesh


© Allerton Press, Inc., 2018

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