An introduction to genetic algorithms
An introduction to genetic algorithms
Matrix computations (3rd ed.)
Space-Time Coding
Improved multiuser detectors employing genetic algorithms in a space-time block coded system
EURASIP Journal on Applied Signal Processing
Diversity techniques to combat fading in WiMAX
WSEAS TRANSACTIONS on COMMUNICATIONS
Analysis of a fixed-complexity sphere decoding method for spatial multiplexing MIMO
WSEAS TRANSACTIONS on COMMUNICATIONS
WSEAS TRANSACTIONS on COMMUNICATIONS
Joint transceiver design for MIMO communications using geometric mean decomposition
IEEE Transactions on Signal Processing - Part I
On the complexity of sphere decoding in digital communications
IEEE Transactions on Signal Processing
On the sphere-decoding algorithm I. Expected complexity
IEEE Transactions on Signal Processing - Part I
Performance of COFDM-based transmitter diversity in a road-to-vehicle communication system
IEEE Transactions on Intelligent Transportation Systems
In-vehicle WLAN radio-frequency communication characterization
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Intelligent Transportation Systems
A universal lattice code decoder for fading channels
IEEE Transactions on Information Theory
On maximum-likelihood detection and the search for the closest lattice point
IEEE Transactions on Information Theory
Diversity-multiplexing tradeoff in multiple-access channels
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
IEEE Journal on Selected Areas in Communications
Analysis and performance of some basic space-time architectures
IEEE Journal on Selected Areas in Communications
Theory of the simple genetic algorithm with α-selection, uniform crossover and bitwise mutation
WSEAS TRANSACTIONS on SYSTEMS
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An efficient multiple-input multiple-output (MIMO) detection (MD) algorithm includes novel, low-complexity, near-optimal and robust scheme is proposed in wireless communications when imperfect noise estimation is considered. By using MIMO technique, capacity increases proportionally as the number of antennas is increased, but the introduced inter-antenna interference (IAI) degrades system performance. To better mitigate IAI, we propose a two-stage procedure to achieve maximum likelihood (ML) performance while keeping at acceptable level of computational complexity. A novel two-stage procedure is proposed as follows that is suitable for either in an overdetermined or an underdetermined MIMO system. In an overdetermined system, interference cancellation is first processed at Stage-1 using sorted QR decomposition (SQRD) followed by Stage-2 that performs a genetic algorithm (GA). In terms of computational complexity, this procedure provides three significant advantages: 1) The SQRD scheme provides excellent interference cancellation so as to largely improve initial setting of GA. 2) By using QRD, fitness value evaluation of GA involves less complexity due to reducing the matrix multiplication. 3) In aspect of diversity knowledge, lately decoded sub-streams expect to have lower error probabilities by using SQRD. In this paper, each mutated gene is decoded from the various diversity gains, termed as a diversity mutation (DM) scheme. To achieve the forementioned three significant advantages in an underdetermined system, on the other hand, we propose zero forcing (ZF) assisted SQRD GA-MD (ZF-SQRD GA-MD) to achieve ML performance. Beside, the proposed two-stage detection procedure is quite robust as it does not rely on noise information. Simulation results show that the proposed two-stage detection procedure can achieve a near-ML performance, but at a low-complexity level.