Performance Analysis of MIMO Schemes in 3GPP Long Term Evolution System

This paper, presents evaluation and analysis of the performance for multiple-input multiple-output (MIMO) schemes in the 3GPP long term evolution (LTE) system. Three performance metrics are considered for the analysis and evaluation, namely, average BER, average channel capacity and average throughput of the system for two different MIMO schemes as defined in LTE. Using the numerical results obtained from the mathematical expressions derived in the paper, we compare the presented schemes and show their significant advantages. Monte-Carlo simulation results of the LTE system are also provided to verify the accuracy of the mathematical analysis. The results for the average throughput of the considered MIMO schemes in LTE are presented for the un-coded case as well as for the coded-case in practical LTE scenarios. In addition, for the sake of comparison, the theoretical capacity limit of the system is also shown.

[1]  Lajos Hanzo,et al.  Adaptive Wireless Transceivers: Turbo-Coded, Turbo-Equalized and Space-Time Coded TDMA, CDMA and OFDM Systems , 2002 .

[2]  Ali Jemmali Performance Evaluation and Analysis of Mimo Schemes in LTE Networks Environment , 2013 .

[3]  Mohamed-Slim Alouini,et al.  Digital Communication Over Fading Channels: A Unified Approach to Performance Analysis , 2000 .

[4]  Mohamed-Slim Alouini,et al.  Adaptive Modulation over Nakagami Fading Channels , 2000, Wirel. Pers. Commun..

[5]  Christoph Günther,et al.  Comment on "Estimate of channel capacity in Rayleigh fading environment , 1996 .

[6]  Candice King,et al.  Fundamentals of wireless communications , 2013, 2014 67th Annual Conference for Protective Relay Engineers.

[7]  Markus Rupp,et al.  Calculation of the spatial preprocessing and link adaption feedback for 3GPP UMTS/LTE , 2010, 2010 Wireless Advanced 2010.

[8]  Markus Rupp,et al.  Mutual information based calculation of the Precoding Matrix Indicator for 3GPP UMTS/LTE , 2010, 2010 International ITG Workshop on Smart Antennas (WSA).

[9]  M. Reza Soleymani,et al.  On the BER Performance of Space-Frequency Block Coded OFDM Systems in Fading MIMO Channels , 2007, IEEE Transactions on Wireless Communications.

[10]  Siavash M. Alamouti,et al.  A simple transmit diversity technique for wireless communications , 1998, IEEE J. Sel. Areas Commun..

[11]  Markus Rupp,et al.  System Level Simulation of LTE Networks , 2010, 2010 IEEE 71st Vehicular Technology Conference.

[12]  Mohamed-Slim Alouini,et al.  A unified approach to the performance analysis of digital communication over generalized fading channels , 1998, Proc. IEEE.

[13]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[14]  Markus Rupp,et al.  Doubly dispersive channel estimation with scalable complexity , 2010, 2010 International ITG Workshop on Smart Antennas (WSA).

[15]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[16]  Lajos Hanzo,et al.  Adaptive Wireless Transceivers , 2002 .

[17]  Markus Rupp,et al.  Simulating the Long Term Evolution physical layer , 2009, 2009 17th European Signal Processing Conference.

[18]  Stefania Sesia,et al.  LTE - The UMTS Long Term Evolution, Second Edition , 2011 .

[19]  David Haccoun,et al.  Performance Analysis of Joint User Scheduling and Antenna Selection Over MIMO Fading Channels , 2011, IEEE Signal Processing Letters.

[20]  Wessam Ajib,et al.  Performance Analysis of Scheduling Schemes for Rate-Adaptive MIMO OSFBC-OFDM Systems , 2010, IEEE Transactions on Vehicular Technology.