Performance Improvement in Spatially Multiplexed MIMO Systems over Weibull-Gamma Fading Channel

Abstract In multiple-input multiple-output (MIMO) systems, spatial demultiplexing at the receiver has its own significance. Thus, several detection techniques have been investigated. There is a tradeoff between computational complexity and optimal performance in most of the detection techniques. One of the detection techniques which gives improved performance and acceptable level of complexity is ordered successive interference cancellation (OSIC) with minimum mean square error (MMSE). However, optimal performance can be achieved by maximum likelihood (ML) detection but at a higher complexity level. Therefore, MMSE-OSIC with candidates (OSIC2) detection is recommended as a solution. In this paper, spatial multiplexed (SM) MIMO systems are considered to evaluate error performance with different detection techniques such as MMSE-OSIC, ML and MMSE-OSIC2 in a composite fading i. e. Weibull-gamma (WG) fading environment. In WG distribution, Weibull and gamma distribution represent multipath and shadowing effects, respectively. Simulation results illustrate that MMSE-OSIC2 detection technique gives the improved symbol error rate (SER) performance which is similar to ML performance and its complexity level approaches to MMSE-OSIC.

[1]  Yong Soo Cho,et al.  MMSE-OSIC² Signal Detection for Spatially Multiplexed MIMO Systems , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.

[2]  Jungwoo Lee,et al.  Low complexity antenna selection for V-BLAST systems with OSIC detection , 2011, EURASIP J. Wirel. Commun. Netw..

[3]  Tsung-Hsien Liu,et al.  Modified fast recursive algorithm for efficient MMSE-SIC detection of the V-BLAST system , 2008, IEEE Transactions on Wireless Communications.

[4]  Ravi Narasimhan,et al.  Error propagation analysis of V-BLAST with channel-estimation errors , 2005, IEEE Transactions on Communications.

[5]  Roger Pierre Fabris Hoefel.  IEEE 802.11n: On performance with MMSE and OSIC spatial division multiplexing transceivers , 2012, 2012 International Symposium on Wireless Communication Systems (ISWCS).

[6]  Huaping Liu,et al.  Error performance of MIMO systems in frequency selective Rayleigh fading channels , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[7]  P. Bithas.  Weibull-gamma composite distribution: alternative multipath/shadowing fading model , 2009 .

[8]  Xiaofeng Tao,et al.  Analytical SER Performance Bound of M-QAM MIMO System with ZF-SIC Receiver , 2008, 2008 IEEE International Conference on Communications.

[9]  Yahia A. Eldemerdash,et al.  Signal Identification for Multiple-Antenna Wireless Systems: Achievements and Challenges , 2016, IEEE Communications Surveys & Tutorials.

[10]  Gerard J. Foschini,et al.  Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas , 1996, Bell Labs Technical Journal.

[11]  Ali Abdi,et al.  K distribution: an appropriate substitute for Rayleigh-lognormal distribution in fading-shadowing wireless channels , 1998 .

[12]  Alexios Balatsoukas-Stimming,et al.  On metric sorting for successive cancellation list decoding of polar codes , 2015, 2015 IEEE International Symposium on Circuits and Systems (ISCAS).

[13]  Reinaldo A. Valenzuela,et al.  Detection algorithm and initial laboratory results using V-BLAST space-time communication architecture , 1999 .

[14]  Markku J. Juntti,et al.  On the performance of space-time coded and spatially multiplexed MIMO systems with linear receivers , 2010, IEEE Transactions on Communications.

[15]  Komal Punia,et al.  Signal detection for Spatially Multiplexed multi input multi output (MIMO) systems , 2014, 2014 International Conference on Communication and Signal Processing.

[16]  Y. Namihira,et al.  Deep sea trial of 1.55 mu m optical fibre submarine cable system , 1988 .

[17]  Pooi Yuen Kam,et al.  On the LLR Metrics for DPSK Modulations Over Two-Symbol Observation Intervals for the Flat Rician Fading Channel , 2015, IEEE Transactions on Communications.

[18]  Zhongding Lei,et al.  A Comparative Study of QRD-M Detection and Sphere Decoding for MIMO-OFDM Systems , 2005, 2005 IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications.

[19]  Mohamed-Slim Alouini,et al.  On the Performance Analysis of Digital Communications over Weibull-Gamma Channels , 2015, 2015 IEEE 81st Vehicular Technology Conference (VTC Spring).

[20]  Yuan-Sun Chu,et al.  A Low-Cost MMSE-SIC Detector for the MIMO System: Algorithm and Hardware Implementation , 2011, IEEE Transactions on Circuits and Systems II: Express Briefs.

[21]  Josef A. Nossek,et al.  On the Capacity of Generalized- $K$ Fading MIMO Channels , 2010, IEEE Transactions on Signal Processing.

[22]  Tsung-Hsien Liu.  Some results for the fast MMSE-SIC detection in spatially multiplexed MIMO systems , 2009, IEEE Transactions on Wireless Communications.

[23]  P. Mohana Shankar,et al.  Fading and Shadowing in Wireless Systems , 2011 .

[24]  H. D. Luke.  Families of polyphase sequences with near-optimal two-valued auto- and crosscorrelation functions , 1992 .

[25]  Hyuncheol Park,et al.  An Improved LLR Computation for QRM-MLD in Coded MIMO Systems , 2007, 2007 IEEE 66th Vehicular Technology Conference.

[26]  F. Hlawatsch,et al.  Detection techniques for MIMO spatial multiplexing systems , 2005 .

[27]  Davinder S. Saini,et al.  SER improvisation of MIMO-MRC system over Weibull-Gamma fading channel , 2015, 2015 International Conference on Signal Processing and Communication (ICSC).

[28]  Chung G. Kang,et al.  MIMO-OFDM Wireless Communications with MATLAB , 2010 .

[29]  Hiroyuki Kawai,et al.  Adaptive control of surviving symbol replica candidates in QRM-MLD for OFDM MIMO multiplexing , 2006, IEEE Journal on Selected Areas in Communications.

[30]  Arogyaswami Paulraj,et al.  Space-time block codes: a capacity perspective , 2000, IEEE Communications Letters.