scholarly journals A CORDIC based QR Decomposition Technique for MIMO Detection

2018 ◽  
Vol 8 (5) ◽  
pp. 2731
Author(s):  
Shirly Edward A. ◽  
Malarvizhi S.
Keyword(s):  
Complexity Analysis ◽  
Multiple Input Multiple Output ◽  
Qr Decomposition ◽  
Mimo Detection ◽  
Hardware Complexity ◽  
Channel Matrix ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Processing Techniques ◽  
Complex Channel

CORDIC based improved real and complex QR Decomposition (QRD) for channel pre-processing operations in (Multiple-Input Multiple-Output) MIMO detectors are presented in this paper. The proposed design utilizes pipelining and parallel processing techniques and reduces the latency and hardware complexity of the module respectively. Computational complexity analysis report shows the superiority of our module by 16% compared to literature. The implementation results reveal that the proposed QRD takes shorter latency compared to literature. The power consumption of 2x2 real channel matrix and 2x2 complex channel matrix was found to be 12mW and 44mW respectively on the state-of-the-art Xilinx Virtex 5 FPGA.

scholarly journals Energy and Information Beamforming in Airborne Massive MIMO System for Wireless Powered Communications

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3540 ◽  
Author(s):  
Yurong Wang ◽  
Aijun Liu ◽  
Kui Xu ◽  
Xiaochen Xia
Keyword(s):  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Hardware Complexity ◽  
Mimo Channels ◽  
Channel State ◽  
Active Antennas ◽  
Large Numbers ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Critical Problems

Energy supply and information backhaul are critical problems for wireless sensor networks deployed in remote places with poor infrastructure. To deal with these problems, this paper proposes an airborne massive multiple-input multiple-output (MIMO) system for wireless energy transfer (WET) and information transmission. An air platform (AP) equipped with a two-dimensional rectangular antenna array is employed to broadcast energy and provide wireless access for ground sensors. By exploiting the statistical property of air-terrestrial MIMO channels, the energy and information beamformers are jointly designed to maximize the average received signal-to-interference-plus-noise ratio (SINR), which gives rise to a statistical max-SINR beamforming scheme. The scheme does not rely on the instantaneous channel state information, but still requires large numbers of RF chains at AP. To deal with this problem, a heuristic strongest-path energy and information beamforming scheme is proposed, which can be implemented in the analog-domain with low computational and hardware complexity. The analysis of the relation between the two schemes reveals that, with proper sensor scheduling, the strongest-path beamforming is equivalent to the statistical max-SINR beamforming when the number of AP antennas tends to infinity. Using the asymptotic approximation of average received SINR at AP, the system parameters, including transmit power, number of active antennas of AP and duration of WET phase, are optimized jointly to maximize the system energy efficiency. The simulation results demonstrate that the proposed schemes achieve a good tradeoff between system performance and complexity.

Depth-First QRD-M Detection Algorithm for MIMO Systems

2013 ◽  
Vol 347-350 ◽  
pp. 3478-3481
Author(s):  
Li Liu ◽  
Jin Kuan Wang ◽  
Xin Song ◽  
Yin Hua Han ◽  
Yu Huan Wang
Keyword(s):  
Ordered Set ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Detection Algorithm ◽  
Qr Decomposition ◽  
Detection Performance ◽  
Detection Scheme ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Ml Detection

Maximum likelihood (ML) detection algorithm for multiple input multiple output (MIMO) systems provided the best bit error rate (BER) performance with heavy calculating complexity. The use of QR decomposition with M-algorithm (QRD-M) had been proposed to provide near-ML detection performance and lower calculating complexity. However, its complexity still grew exponentially with increasing dimension of the transmitted signal. To reduce the problem, an improved detection scheme was proposed here. After constructing the tree detecting model of MIMO systems, the ML search of one layer was done, the branch metrics were calculated and sorted, which gave an ordered set of the layer, then depth-first search were used to search the left layers with termination methods. The proposed algorithm provides near QRD-M detection performance.

scholarly journals Hardware Development of Baseband Transceiver and FPGA-Based Testbed in 88 and 22 MIMO-OFDM Systems

1970 ◽  
Vol 6 (1) ◽  
pp. 64-71 ◽  
Author(s):  
Shingo Yoshizawa ◽  
Yoshikazu Miyanaga
Keyword(s):  
Video Transmission ◽  
Multiple Input Multiple Output ◽  
Ofdm Systems ◽  
Mimo Detection ◽  
Communication Capacity ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Ofdm ◽  
Frequency Multiplexing ◽  
Spatial Division Multiplexing

Multiple-input multiple-output orthogonal frequency multiplexing (MIMO-OFDM) is powerfulin enhancing communication capacity or reliance. The IEEE802.11n standard defines use of four spatial streams in spatial division multiplexing (SDM). The task group of IEEE802.11ac will extend it to eight spatial streams. We present an 88 MIMOOFDM baseband transceiver compatible with the IEEE802.11ac specification. Two 88 MMSE MIMO detectors based on Streassen’s matrix inversion have been designed for real-time MIMO detection. To demonstrate MIMO-OFDM transmission, we have prototyped a FPGA-based testbed in 22 MIMOOFDM for field experiment and video transmission.

scholarly journals Reduced Complexity by Combining Norm Based Ordering MMSE-BSIDE Detection in MIMO Systems

2017 ◽  
Vol 63 (3) ◽  
pp. 305-308
Author(s):  
Ramya Jothikumar ◽  
Nakkeeran Rangaswamy
Keyword(s):  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Detection Methods ◽  
Mimo Detection ◽  
Detection Scheme ◽  
Tree Traversal ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Simulation Results

AbstractThe breadth first signal decoder (BSIDE) is well known for its optimal maximum likelihood (ML) performance with lesser complexity. In this paper, we analyze a multiple-input multiple-output (MIMO) detection scheme that combines; column norm based ordering minimum mean square error (MMSE) and BSIDE detection methods. The investigation is carried out with a breadth first tree traversal technique, where the computational complexity encountered at the lower layers of the tree is high. This can be eliminated by carrying detection in the lower half of the tree structure using MMSE and upper half using BSIDE, after rearranging the column of the channel using norm calculation. The simulation results show that this approach achieves 22% of complexity reduction for 2×2 and 50% for 4×4 MIMO systems without any degradation in the performance.

Reduced Complexity FSD Algorithm for MIMO Detection

2012 ◽  
Vol 195-196 ◽  
pp. 259-264
Author(s):  
Xin Yu Mao ◽  
Shu Bo Ren ◽  
Hai Ge Xiang
Keyword(s):  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Antenna System ◽  
Sphere Decoding ◽  
Mimo Detection ◽  
Time Simulation ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Simulation Results ◽  
High Order Modulation

Detection is a major challenge for the utilization of multiple-input multiple-output (MIMO) system. Even the fixed sphere decoding (FSD), which is known for its simplicity in calculation, requests too much computation in high order modulation and large number antenna system especially for mobile battery-operated devices. In this paper, a reduced FSD algorithm is proposed to simplify the calculation complexity of the FSD while maintaining the performance at the same time. Simulation results in a 4×4, 16-QAM system show that up to 89% calculation can be saved while the performance drop is less than 0.1dB when SNR=24.

scholarly journals Amplitude Constrained MIMO Channels: Properties of Optimal Input Distributions and Bounds on the Capacity

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 200 ◽  
Author(s):  
Alex Dytso ◽  
Mario Goldenbaum ◽  
H. Poor ◽  
Shlomo Shamai (Shitz)
Keyword(s):  
General Structure ◽  
Multiple Input Multiple Output ◽  
Average Power ◽  
Upper And Lower Bounds ◽  
Channel Matrix ◽  
Input Space ◽  
Input Distribution ◽  
Channel Input ◽  
Multiple Input ◽  
Input Multiple Output

In this work, the capacity of multiple-input multiple-output channels that are subject to constraints on the support of the input is studied. The paper consists of two parts. The first part focuses on the general structure of capacity-achieving input distributions. Known results are surveyed and several new results are provided. With regard to the latter, it is shown that the support of a capacity-achieving input distribution is a small set in both a topological and a measure theoretical sense. Moreover, explicit conditions on the channel input space and the channel matrix are found such that the support of a capacity-achieving input distribution is concentrated on the boundary of the input space only. The second part of this paper surveys known bounds on the capacity and provides several novel upper and lower bounds for channels with arbitrary constraints on the support of the channel input symbols. As an immediate practical application, the special case of multiple-input multiple-output channels with amplitude constraints is considered. The bounds are shown to be within a constant gap to the capacity if the channel matrix is invertible and are tight in the high amplitude regime for arbitrary channel matrices. Moreover, in the regime of high amplitudes, it is shown that the capacity scales linearly with the minimum between the number of transmit and receive antennas, similar to the case of average power-constrained inputs.

On Optimal Constellation Shaping for Wireless MIMO Relay Networks Based on Complex Field Network Coding

2014 ◽  
Vol 490-491 ◽  
pp. 1410-1414
Author(s):  
Xin Zhou ◽  
Yi Jun Guo ◽  
Jian Jun Hao
Keyword(s):  
Network Coding ◽  
Multiple Input Multiple Output ◽  
General System ◽  
Destination Node ◽  
Relay Channel ◽  
Mimo Detection ◽  
Similar System ◽  
Constellation Shaping ◽  
Multiple Input ◽  
Input Multiple Output

Network Coding (NC) is a promising technique that can maximize the network throughput. Multiple-Input-Multiple-Output (MIMO) detection technique is always combined with NC because they are both based on a similar system description. Two-way relay channel (TWRC) is the most common scene for the research on NC. However, TWRC is not a general case since it requires both users have information to exchange simultaneously. In this paper, a more general system model which adds a destination node is proposed. Based on this scene, for symmetrical and asymmetrical modulation schemes, we maximize the minimum Euclidean distance of the superposed constellation. The destination node never needs to have a packet exchange with the relay. Excellent performance has been proved by the theory analysis and simulation results.

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