Nakagami-m approximations for multiple-input multiple-output singular value decomposition transmissions

This paper evaluates the performance of closed loop multiple input multiple output power line communication (CL MIMO PLC) system based on enhanced zero-forcing (ZF) equalizer. In this work, the two-sided Jacobi (TSJ) algorithm has been investigated for the computation of singular value decomposition of the channel matrix. Quantized parameters are feedback from the receiver to the transmitter for precoding process. Numerous simplifications are introduced for the reduction of the algorithm complexity. The performance of the CL MIMO PLC is evaluated in terms of bit error rate (BER), constellation error vector magnitude (EVM), and mean square error (MSE) between the constructed SVD matrices and Matlab computed ones.

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Decoupling of Broadband Optical MIMO Systems Using the Multiple Shift SBR2 Algorithm

International Journal of Advances in Telecommunications Electrotechnics Signals and Systems ◽

10.11601/ijates.v6i1.207 ◽

2017 ◽

Vol 6 (1) ◽

pp. 30

Author(s):

Zeliang Wang ◽

André Sandmann ◽

John G. McWhirter ◽

Andreas Ahrens

Keyword(s):

Bit Error Rate ◽

Mimo Systems ◽

Multiple Input Multiple Output ◽

Singular Value ◽

Mimo Channel ◽

Multiple Input ◽

Channel Interference ◽

Input Multiple Output ◽

Value Decomposition ◽

Multi Mode

Polynomial singular value decomposition (PSVD) plays a very important role in broadband multiple-input multiple-output (MIMO) systems. One of its applications lies in the decoupling of MIMO convolutive mixing channel matrixin order to recover the transmitted signals corrupted by the channel interference (CI) at the receiver. In this paper, a novel algorithm, known as multiple shift second order sequential best rotation (MS-SBR2), is proposed to compute the approximate PSVD of the broadband MIMO channel matrix. Experimental examples, including a measured (2 × 2) optical MIMO channel impulse response using the multi-mode fiber (MMF) testbed, are presented to examine the proposed algorithm. Bit error rate (BER) performances are evaluated among different transmission schemes. In addition, power allocation (PA) schemes are investigated to further optimize the BER performance.

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Broadband over Power Lines Systems Convergence: Multiple-Input Multiple-Output Communications Analysis of Overhead and Underground Low-Voltage and Medium-Voltage BPL Networks

ISRN Power Engineering ◽

10.1155/2013/517940 ◽

2013 ◽

Vol 2013 ◽

pp. 1-30 ◽

Cited By ~ 9

Author(s):

Athanasios G. Lazaropoulos

Keyword(s):

Modal Analysis ◽

Review Paper ◽

Low Voltage ◽

Multiple Input Multiple Output ◽

Power Lines ◽

Mimo Channels ◽

Medium Voltage ◽

Multiple Input ◽

Input Multiple Output ◽

Value Decomposition

This review paper reveals the broadband potential of overhead and underground low-voltage (LV) and medium-voltage (MV) broadband over power lines (BPL) networks associated with multiple-input multiple-output (MIMO) technology. The contribution of this review paper is fourfold. First, the unified value decomposition (UVD) modal analysis is introduced. UVD modal analysis is a new technique that unifies eigenvalue decomposition (EVD) and singular value decomposition (SVD) modal analyses achieving the common handling of traditional SISO/BPL and upcoming MIMO/BPL systems. The validity of UVD modal analysis is examined by comparing its simulation results with those of other exact analytical models. Second, based on the proposed UVD modal analysis, the MIMO channels of overhead and underground LV and MV BPL networks (distribution BPL networks) are investigated with regard to their inherent characteristics. Towards that direction, an extended collection of well-validated metrics from the communications literature, such as channel attenuation, average channel gain (ACG), root-mean-square delay spread (RMS-DS), coherence bandwidth (CB), cumulative capacity, capacity complementary cumulative distribution function (CCDF), and capacity gain (GC), is first applied in overhead and underground MIMO/LV and MIMO/MV BPL channels and systems. It is found that the results of the aforementioned metrics portfolio depend drastically on the frequency, the power grid type (either overhead or underground, either LV or MV), the MIMO scheme configuration properties, the MTL configuration, the physical properties of the cables used, the end-to-end distance, and the number, the electrical length, and the terminations of the branches encountered along the end-to-end BPL signal propagation. Third, three interesting findings concerning the statistical properties of MIMO channels of distribution BPL networks are demonstrated, namely, (i) the ACG, RMS-DS, and cumulative capacity lognormal distributions; (ii) the correlation between RMS-DS and ACG; and (iii) the correlation between RMS-DS and CB. By fitting the numerical results, unified regression distributions appropriate for MIMO/BPL channels and systems are proposed. These three fundamental properties can play significant role in the evaluation of recently proposed statistical channel models for various BPL systems. Fourth, the potential of transformation of overhead and underground LV/BPL and MV/BPL distribution grids to an alternative solution to fiber-to-the-building (FTTB) technology is first revealed. By examining the capacity characteristics of various MIMO scheme configurations and by comparing these capacity results against SISO ones, a new promising urban backbone network seems to be born in a smart grid (SG) environment.

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Design of Massive Multiuser MIMO System to Mitigate Inter Antenna Interference and Multiuser Interference in 5G Wireless Networks

Journal of Communications ◽

10.12720/jcm.15.9.693-701 ◽

2020 ◽

pp. 693-701 ◽

Cited By ~ 1

Author(s):

Naga Raju Challa ◽

◽

Kalapraveen Bagadi

Keyword(s):

Communication Networks ◽

Mimo System ◽

Multiple Input Multiple Output ◽

Matrix Computations ◽

User Terminal ◽

Multiple Input ◽

Input Multiple Output ◽

Major Factors ◽

Value Decomposition ◽

User Interference

Massive Multi-user Multiple Input Multiple Output (MU‒MIMO) system is aimed to improve throughput and spectral efficiency in 5G communication networks. Inter-antenna Interference (IAI) and Multi-user Interference (MUI) are two major factors that influence the performance of MU–MIMO system. IAI arises due to closely spaced multiple antennas at each User Terminal (UT), whereas MUI is generated when one UT comes in the vicinity of another UT of the same cellular network. IAI can be mitigated by the use of a pre-coding scheme such as Singular Value Decomposition (SVD) and MUI can be cancelled through efficient Multi-user Detection (MUD) schemes. The highly complex and optimal Maximum Likelihood (ML) detector involves a large number of computations, especially when in massive structures. Therefore, the local search-based algorithm such as Likelihood Ascent Search (LAS) has been found to be a better alternative for mitigation of MUI, as it results in near optimal performance using lesser number of matrix computations. Most of the literature have been aimed at mitigating either IAI or MUI, whereas the proposed work presents SVD pre-coding and LAS MUD to mitigate both IAI and MUI. Simulation results indicate that the proposed scheme can attain near-optimal bit error rate (BER) performance with fewer computations.

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Research of Improved Algorithm for MIMO Channel Estimation

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.475-476.893 ◽

2013 ◽

Vol 475-476 ◽

pp. 893-899

Author(s):

Miao Miao Chang ◽

Jin He Zhou ◽

Ju Rong Wang

Keyword(s):

Singular Value Decomposition ◽

Channel Estimation ◽

Mean Square Error ◽

Minimum Mean Square Error ◽

Multiple Input Multiple Output ◽

Estimation Algorithm ◽

Singular Value ◽

Mimo Channel ◽

Mean Square ◽

Value Decomposition

We introduced an improved singular value decomposition (SVD) channel estimation algorithm for multiple-input multiple-output (MIMO) wireless communication system. The algorithm is supposed to solve the issue that the channel estimation result is not accurate when the training sequences have some 0 elements. The improvement is also applicable in the other channel estimation algorithms. We made some comparisons between the linear least squares (LS) and the linear minimum mean square error (LMMSE) channel estimation, the traditional singular value decomposition and the improved SVD algorithm to demonstrate the efficiency. Results show that the proposed improved SVD algorithm has better performance in mean square error (MSE) and bit error rate (BER) of channel estimation and the estimated values approach the actual channel state.

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