A Low Complexity Quantization Technique for Virtual MIMO Systems

By means of wireless cooperation, Virtual Multiple- Input Multiple-Output (V-MIMO) systems provide significant enhancements in terms of spectral efficiency and performance. A large V-MIMO system that implements bit-interleaved coded modulation (BICM) transmission and compress-and-forward (CF) cooperation is considered. Since, constructing a reliable codebook is the most computationally complex task performed by the relay nodes, in this paper, we evaluate two low complexity quantization techniques. A comparison in terms of the codebook design and overhead complexity is presented. Error performance results show that the Lloyd - Max algorithm (LM-SQ) is simpler to design and can achieve a performance comparable to optimal Voronoi Vector Quantization (V-VQ). Further, Uniform Scalar Quantization (U-SQ) is also considered, as its low complexity makes it particularly suitable for the upcoming large wireless systems.

[1]  Reza Hoshyar,et al.  A Novel Quantization Scheme in Compress-and-Forward Relay System , 2009, VTC Spring 2009 - IEEE 69th Vehicular Technology Conference.

[2]  Kin K. Leung,et al.  Cooperative Transmission Protocols for Wireless Broadcast Channels , 2010, IEEE Transactions on Wireless Communications.

[3]  R. Gray,et al.  Vector quantization , 1984, IEEE ASSP Magazine.

[4]  张胜利 Channel Quantization Based Physical-layer Network Coding , 2013 .

[5]  Aditya K. Jagannatham,et al.  Optimal Wake-up Scheduling for PSM Delay Minimization in Mobile Wireless Networks , 2013, IEEE Wireless Communications Letters.

[6]  Gerald Matz,et al.  Performance Assessment of MIMO-BICM Demodulators Based on Mutual Information , 2012, IEEE Transactions on Signal Processing.

[7]  Cheng-Xiang Wang,et al.  Energy-Spectral Efficiency Trade-Off in Virtual MIMO Cellular Systems , 2013, IEEE Journal on Selected Areas in Communications.

[8]  Philip Ogunbona,et al.  On the computational complexity of the LBG and PNN algorithms , 1997, IEEE Trans. Image Process..

[9]  Ron Dabora,et al.  On the Role of Estimate-and-Forward With Time Sharing in Cooperative Communication , 2006, IEEE Transactions on Information Theory.

[10]  John S. Thompson,et al.  Performance assessment of virtual multiple-input multiple-output systems with compress-and-forward cooperation , 2012, IET Commun..

[11]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[12]  Jing Jiang,et al.  Design and analysis of compress-and-forward cooperation in a virtual-MIMO detection system , 2010, 2010 IEEE Globecom Workshops.

[13]  Muhammad Ali Imran,et al.  Energy Efficiency and Optimal Power Allocation in Virtual-MIMO Systems , 2012, 2012 IEEE Vehicular Technology Conference (VTC Fall).

[14]  Muhammad Ali Imran,et al.  Energy-Efficiency Analysis and Optimization for Virtual-MIMO Systems , 2014, IEEE Transactions on Vehicular Technology.

[15]  Anders Høst-Madsen,et al.  Capacity bounds for Cooperative diversity , 2006, IEEE Transactions on Information Theory.