Detection For MIMO-OFDM Systems Research Articles

Performance Analysis of Efficient and Low Complexity MIMO-OFDM System Using Modified V-BLAST

Background and Objective: To analyze the performance of MIMO-OFDM system, VBLAST detection suffers from computational complexity as well as high BER. Methods: To improve the BER performance and to reduce the computational complexity of receiver, we propose a modified VBLAST detection in MIMO-OFDM Systems. Results: Simulation using MATLAB shows the improvement in computational complexity and in BER. Conclusion: This modified VBLAST reduces the complexity of MIMO-OFDM System to 44.2% and improvement in BER as compared to conventional VBLAST based MIMO-OFDM System.

Novel MIMO Detection With Improved Complexity for Near-ML Detection in MIMO-OFDM Systems

In this paper, a novel efficient algorithm for MIMO detection in MIMO-OFDM systems has been proposed. This paper also shows that the complexity can be greatly reduced by applying the threshold in the breadth-first tree search algorithm step to eliminating paths. That is, this algorithm derives thresholds based on the LR-aided nonlinear algorithm and performs a simple tree search detection algorithm. This algorithm requires a lower computational complexity than the conventional QRD-M detection algorithm and achieves the same bit error performance. After the novel detection algorithm is proposed, this paper applies this algorithm to the MIMO-OFDM system for performance comparison in terms of error performance and complexity. In many cases of MIMO-OFDM receivers, the proposed method will be an excellent option for implementation.

Geneti Algorithm Optimization Tool for Channel Estimation and Symbol Detection in Mimo-OFDM Systems

Geneti Algorithm Optimization Tool for Channel Estimation and Symbol Detection in Mimo-OFDM Systems

Optimal SP Training and Precoding Designs for Channel Estimation and Symbol Detection in MIMO-OFDM Systems

Based on convex programming for optimization, a closed-from solution of superimposed (SP) training on linearly precoded data for jointly optimal channel estimation and symbol detection is proposed in this paper for MIMO-OFDM systems. The newly designed method not only efficiently identifies the frequency-selective fading channel but also effectively enhances the symbol detection. Although linearly precoding technique is employed and protects the transmitted data over the multi-path MIMO wireless channels, the precoded data is always arithmetically added to the training sequence to prevail transmission bandwidth. Analytical and numerical results confirm that the proposed design efficiently estimates the wireless fading channel and effectively recovers the source data symbols.

On Detection in MIMO-OFDM Systems Over Highly Mobile Wireless Channels

High mobility support of multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems plays a major role in wireless communication systems. Conventional detection approaches for MIMO-OFDM systems assume the channel is constant for at least one OFDM symbol duration. However, the time variation of the channel on account of mobility over an OFDM symbol period causes a loss of subchannel orthogonality which results in inter-carrier interference. In this paper, we propose the space alternating generalized expectation maximization (SAGE) based signal detection for MIMO-OFDM systems and compared by the zero forcing (ZF), minimum mean square error (MMSE), vertical Bell laboratories layered space-time (VBLAST) detection methods by considering complexity and performance tradeoffs. Simulation results show that the SAGE based detection has comparable performance with the VBLAST while needs lower computational complexity. It is also shown that both SAGE and VBLAST have a clear BER performance advantage over the MMSE and ZF detections. We also investigate the sensitivity of detection MIMO-OFDM signals to channel estimation errors by the application of a simple frequency domain based pilot based channel estimation. It is shown that the superiority of the SAGE scheme is also valid in the case of channel imperfections.

ITERATIVE QR DECOMPOSTION CHANNEL ESTIMATION FOR MIMO-OFDM SYSTEMS

Channel estimation algorithms have a key role in si gnal detection in MIMO-OFDM systems. In this system , the number of channel components which need to be estimated is much more than conventional SISO wireless systems. Consequent ly, the computational process of channel estimation is highly intensive. In addition, the high performance channel estimatio n algorithms mostly suffer from high computational complexity. In the other words, the system undergoes intensive computations if high performance efficiency is desired. However, there is an alternative solution to achieve both high performance efficiency and rel atively low level of computational complexity. In this solution, high ef ficient channel estimation is firstly designed, and then it is simplified using alternative mathematical expressions. In this paper , Iterative channel estimation based on QR decompos ition for MIMO-OFDM systems is proposed. From simulation results, the i terative QRD channel estimation algorithm can provi de better mean-square-error and bit error rate performance than conventional me thods.

Symbol detection using the differential evolution algorithm in MIMO-OFDM systems

Channel estimation and symbol detection in multiple-input and multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems are essential tasks. Although the maximum likelihood (ML) detector reveals excellent performance for symbol detection, the computational complexity of this algorithm is extremely high in systems with more transmitter antennas and high-order constellation size. In this paper, we propose the differential evolution (DE) algorithm in order to reduce the search space of the ML detector and the computational complexity of symbol detection in MIMO-OFDM systems. The DE algorithm is also compared to some heuristic approaches, such as the genetic algorithm and particle swarm optimization. According to the simulation results, the DE has the advantage of significantly less complexity and is closer to the optimal solution.

Super-low-complexity QR decomposition-M detection scheme for MIMO-OFDM systems

This study proposes a super-low-complexity detection scheme to control the surviving symbols at each stage of near-maximum-likelihood detection for MIMO-OFDM systems. The new scheme can reduce not only the number of surviving symbol replica candidates at each stage, but also the number of Euclidian distance calculations required for selecting each surviving symbol replica candidate. The former is implemented by adaptively controlling the number of survived candidates according to the estimated level of interference plus noise while the latter is performed by a quadrant detection method. Simulation results show that the proposed scheme has a much lower complexity than that of conventional approaches.

Combined QRD-M and DFE detection technique for simple and efficient signal detection in MIMO-OFDM systems

An efficient MIMO signal detection technique with low complexity is presented for MIMO-OFDM systems. The proposed technique has a feature of combined QRD-M and DFE detection. In our detection technique with M transmit antennas, after QRD-M detection is executed for first T detection steps, DFE detection is executed for last M - T detection steps. This approach is simple and has low complexity, because the computations for QRD-M is limited by the newly adopted parameter T. From simulation results, the complexity of the proposed technique with 4 times 4 and T = 2 is reduced by 61% compared with that of the conventional QRD-M at the expense of about 0.7dB degradation of BER performance at BER=10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> . The simulations are executed in Ricean and Rayleigh channel models. And the simulation of proposed technique is executed by using estimated channel. Through the simulations, it is ascertained that the proposed detection can be used for Ricean and Rayleigh channel models as well as estimated channel.

Space frequency block coded turbo-BLAST detection for MIMO-OFDM systems

A new bandwidth efficient technique that achieves high data rates over the wideband wireless channel is proposed. This method is targeted for the MIMO-OFDM system that achieves transmit diversity through space frequency block code and capacity enhancement through iterative detection and MAP decoding. The new method shows great improvement compared to the conventional V-BLAST system.