Grover's Quantum Search Based Data Detection Algorithm for MIMO System

Abstract Maximum like-lihood (ML) algorithm is the optimal detection scheme for the data detection of multiple-input multiple-output (MIMO) communication systems, but it has a high complexity in its preprocessing. For good performance and low complexity, a new Grover’s Quantum Search (GS) based data detection algorithm for MIMO system is proposed. It can increase the probability amplitude of solutions while reducing the probability amplitude of non-solutions. By Grover’s iterative process, the probability amplitude of solutions can reach maximum. So it can get the solutions after measurement with a high probability. The simulation results show that the proposed data detection algorithm for MIMO system has a very close to ML based data detection in Bit Error Rate (BER) performance, but it has lower complexity than ML based data detection algorithm.

[1]  Hyuncheol Park,et al.  Bit error performance of convolutional coded MIMO system with linear MMSE receiver , 2009, IEEE Transactions on Wireless Communications.

[2]  Lov K. Grover.  A fast quantum mechanical algorithm for database search , 1996, STOC '96.

[3]  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.

[4]  Liang Zhou,et al.  A New Real-Coded Quantum-Inspired Evolutionary Algorithm , 2011 .

[5]  James K. Cavers,et al.  An iterative groupwise multiuser detector for overloaded MIMO applications , 2007, IEEE Transactions on Wireless Communications.

[6]  Henk Wymeersch,et al.  Low Complexity MIMO Detection Based on the Slowest Descent Method , 2007, IEEE Communications Letters.

[7]  Kiran Kuchi,et al.  Performance Analysis of ML Detection in MIMO Systems with Co-Channel Interference , 2011, IEEE Communications Letters.

[8]  JianGang Yang,et al.  Intelligence Optimization Algorithms: A Survey , 2011 .

[9]  Tadashi Fujino,et al.  A Gram-Schmidt Based Lattice-Reduction Aided MMSE Detection in MIMO Systems , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[10]  Thierry Paul,et al.  Quantum computation and quantum information , 2007, Mathematical Structures in Computer Science.

[11]  Josef A. Nossek,et al.  ZF Detectors over Correlated K Fading MIMO Channels , 2011, IEEE Transactions on Communications.

[12]  Helmut Bölcskei,et al.  An overview of MIMO communications - a key to gigabit wireless , 2004, Proceedings of the IEEE.