Study of LB-SE with Perfect CSI in Hyper MIMO


Цитировать

Полный текст

Открытый доступ Открытый доступ
Доступ закрыт Доступ предоставлен
Доступ закрыт Только для подписчиков

Аннотация

Analytical consideration of lower bound (LB) analysis of the spectral efficiency (SE) of downlink transmission of Hyper MIMO (H-MIMO) system is important to obtain insights in the role of various factors that are involved. In this paper, we derived a mathematical expression for lower bound of the SE of an H-MIMO system with linear precoding techniques such as zero-forcing (ZF) and minimum mean square error (MMSE). The analysis of SE considers three joint user and antenna scheduling algorithms such as semi-orthogonal, random, and distance based user scheduling algorithms, whereas the antennas are selected based on maximum SNR with scheduled users. The channel between a user and a transmitter is assumed to have characteristics of small and large scale fading (SSF and LSF) with Rayleigh distributed block fading model. We investigate the effect of variation of transmit power, number of base station antennas M, and the radius of the cell on the SE. We simulate the downlink transmission of H-MIMO system and compare the simulation and analytical results. It is observed that the trends of variation of both results with the variation of different factors are similar, and the difference between the simulated and analytical LB-SE is approximately 1–1.5 bits. In this case the analytical LB is the smaller of the two.

Об авторах

Tasher Sheikh

North Eastern Regional Institute of Science and Technology

Автор, ответственный за переписку.
Email: tasher372@gmail.com
Индия, Nirjuli, Arunachal Pradesh

Joyatri Bora

North Eastern Regional Institute of Science and Technology

Автор, ответственный за переписку.
Email: jb@nerist.ac.in
Индия, Nirjuli, Arunachal Pradesh

Md. Hussain

North Eastern Regional Institute of Science and Technology

Автор, ответственный за переписку.
Email: ah@nerist.ac.in
Индия, Nirjuli, Arunachal Pradesh


© Allerton Press, Inc., 2019

Данный сайт использует cookie-файлы

Продолжая использовать наш сайт, вы даете согласие на обработку файлов cookie, которые обеспечивают правильную работу сайта.

О куки-файлах