This paper analyzes the cell edge mobile user performance in the downlink cellular system. We develop frame-work for coverage probability and spectral e±ciency. In particular, we analyzed the performance of multi-antenna mobile users under multi-antenna base stations (BSs). The expressions of coverage probability and spectral e±ciency are derived for cell edge user using stochastic geometry. We investigate how much the performance of cell edge user is improved when distances connecting BSs and cell edge users are modeled with cell edge null probability distribution. The probability of coverage and spectral e±ciency is studied using zero-forcing beam-forming and the performance metrics are compared between coordinated scheduling (CS) and without coordinated scheduling (w/o CS). The interesting observation from our results is that the edge user coverage and rate is closely approaching towards the inner cell typical mobile user's rate and coverage, and the performance is veri¯ed with relative probability of coverage gain analysis. J CIRCUIT SYST COMP 2015.24. Downloaded from www.worldscientific.com by NATIONAL UNIVERSITY OF SINGAPORE on 10/07/15. For personal use only.metrics. 1 Out of the many, one is explicitly present in providing connection to the users called probability of coverage and the other is related to the spectral e±ciency. The network average data rate is analyzed by spectral e±ciency which fundamentally relates the spectrum use with growing demands for the service. In Ref. 2, they proved that the Qos plays vital role in cellular optimization, system planning and analysis. The other Qos metric is the diversity gain which is de¯ned as rate of decay of outage probability in the high coverage regime. The diversity gain is studied for heterogeneous joint transmission networks in Ref. 3.Recent research and communication standards have focused on multi-antenna in base station (BS) and mobile unit (MU) in Ref. 4. The prime objective of multiantenna communications is to increase the data rates and reliability in cellular communication networks thereby providing good Qos. The multiple-input multipleoutput (MIMO) techniques for cellular systems are a®ected by intercell interference. The intercell interference can be avoided or aligned at the transmitter side and/or removed at the receiver side by way of joint processing. By using the richness of environment one such an alignment technique is developed in Ref. 5. The intercell interference is mitigated by many approaches in the past by way of sharing required information through backhaul. MIMO can take various strategies to cancel out the intercell interference like dirty paper coding (DPC), Eigen beamforming and zero-forcing beamforming, etc. DPC requires the full channel state information at the transmitter side which is di±cult to achieve and performs encoding among the users in an ordered manner, and thereby eliminates interference at the transmitter side in Ref. 6. Methodology was also developed to measure the statistical variation of the interference power...
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