A common framework for ML detection of spatially multiplexed and space time coded MIMO signals and reducing its computational complexity

2016 ◽  
Author(s):  
Nanda Kishore Chavali ◽  
Sheela Mounika ◽  
Kiran Kuchi
Keyword(s):  
Computational Complexity ◽  
Space Time ◽  
Common Framework ◽  
Ml Detection

Новый критерий оптимальности пространственно-временных матриц

2020 ◽  
Author(s):  
A.A. Reznev ◽  
V.B. Kreyndelin
Keyword(s):  
Computational Complexity ◽  
Large Scale ◽  
Noise Immunity ◽  
Optimality Criterion ◽  
Mimo Systems ◽  
Optimality Criteria ◽  
Space Time ◽  
Space Time Codes ◽  
Golden Code ◽  
New Criterion

The application of optimality criteria for the study of space-time codes is considered. Known rank and determinant criteria are described. The computational complexity of determinant criteria is presented taking into account some estimation of the real CPUs specifications. An algorithm for calculating a new optimality criterion is described. The computational complexity of the new optimality criterion is evaluated. The new criterion is applied to the study of the space-time Golden matrix. The obtained criterion value is used to modify the Golden code. The modeling for Golden code demonstrates that criterion works and gives us better levels for noise immunity. The proposed optimality criterion is acceptable in terms of computational complexity even for a large number of antennas, which is typical for large-scale MIMO systems. Рассматривается применение критериев оптимальности для исследования пространственно-временных кодов.Описаны известные ранговый и детерминантный критерии. Для детерминантного критерия оценена вычислительная сложность с учетом определения специальных высокопроизводительных процессоров. Описан алгоритм расчета нового критерия оптимальности. Проведена оценка вычислительной сложности нового критерия оптимальности. Новый критерий применен для исследования пространственно-временной матрицы Голден. Полученное значение критерия использовано для модификациикода Голден. Продемонстрированы кривые помехоустойчивости для кода Голден и кода Голден с модифицированным параметром, получен энергетический выигрыш. Предложенный критерий оптимальности приемлем с точки зрения вычислительнойсложности даже при большом числе антенн, характерном для систем широкомасштабного MIMO.

scholarly journals Computational Complexity of Decoding Orthogonal Space-Time Block Codes

2011 ◽  
Vol 59 (4) ◽  
pp. 936-941 ◽  
Author(s):  
Ender Ayanoglu ◽  
Erik G. Larsson ◽  
Eleftherios Karipidis
Keyword(s):  
Computational Complexity ◽  
Block Codes ◽  
Space Time ◽  
Time Block ◽  
Space Time Block Codes ◽  
Orthogonal Space

Space-Time-Coded Adaptive Spatial Modulation in Wireless MIMO Communication Systems

Frequenz ◽  
2015 ◽  
Vol 69 (7-8) ◽  
Author(s):  
Shilian Wang ◽  
Fanggang Wang ◽  
Zhao Li
Keyword(s):  
Communication Systems ◽  
Adaptive Modulation ◽  
Antenna System ◽  
Space Time ◽  
Spatial Modulation ◽  
Order Selection ◽  
Error Performance ◽  
Alamouti Code ◽  
Detection Schemes ◽  
Ml Detection

AbstractIn this paper, we consider a wireless multi-antenna system using a promising technique, i.e., spatial modulation, and propose an adaptive spatial modulation (ASM) scheme embedded Alamouti space-time block coding (STBC). Instead of selecting one active antenna in each transmission in conventional ASM, we activate two antennas as one antenna group simultaneously to encode the information bits into Alamouti code blocks, each of which needs two channels used. Two detection schemes are presented in different channel conditions, i.e., the maximum likelihood (ML) detection and an adaptive modulation-order selection algorithm. Simulation results show that the proposed scheme improves the error performance and provides larger diversity gain compared to conventional spatial modulation and adaptive spatial modulation.

scholarly journals An Efficient Broadband Adaptive Beamformer without Presteering Delays

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1100
Author(s):  
Ming Zhang ◽  
Xiaojian Wang ◽  
Anxue Zhang
Keyword(s):  
Computational Complexity ◽  
Computational Cost ◽  
Weight Vector ◽  
Space Time ◽  
Constraint Matrix ◽  
Matrix Operations ◽  
Frequency Constraint ◽  
Simpler Algorithm ◽  
Specific Direction ◽  
Constraint Method

Broadband adaptive beamformers have been widely used in many areas due to their ability of filtering signals in space domain as well as in frequency domain. However, the space-time array employed in broadband beamformers requires presteering delays to align the signals coming from a specific direction. Because the presteering delays are direction dependent, it is difficult to make precise delays in practice. A common way to eliminate the presteering delays is imposing constraints on the weight vector of the space-time array. However, the structure of the constraint matrix is not taken into account in the existing methods, leading to a computational complexity of O(N2) when updating the weight vector. In this paper, we describe a new kind of constraint method in time domain that preserves the block diagonal structure of the constraint matrix. Based on this structure, we design an efficient weight vector update algorithm that has a computational complexity of O(N). In addition, the proposed algorithm does not contain matrix operations (only scalar and vector operations are involved), making it easy to be implemented in chips such as FPGA. Moreover, the constraint accuracy of the proposed method is as high as the frequency constraint method when the fractional bandwidth of the signal is smaller than 10%. Numerical experiments show that our method achieves the same performance of the state-of-the-art methods while keeping a simpler algorithm structure and a lower computational cost.

Space-Time Adaptive Processing and Jamming

2018 ◽  
pp. 38-62
Keyword(s):  
Signal Processing ◽  
Computational Complexity ◽  
Covariance Matrix ◽  
Basic Concept ◽  
Processing Technique ◽  
Space Time ◽  
Adaptive Processing ◽  
Signal Processing Technique ◽  
Space Time Adaptive Processing ◽  
Established Technique

Space-time adaptive processing (STAP) has been a well-established technique, whose basic concept and theory are first put forward by Brennan and Reed. However, it is difficult to implement in the practical system because of the computational complexity and the sample limitation for estimating the clutter covariance matrix. STAP is a modern signal processing technique that can improve target detectability in the presence of a strong clutter Klemm.

SS-BMUSIC Algorithm for Space-Time 2D Signal Model

2014 ◽  
Vol 654 ◽  
pp. 346-351 ◽  
Author(s):  
Yang Jun ◽  
Qi Feng
Keyword(s):  
Computational Complexity ◽  
Space Time ◽  
Smoothing Effect ◽  
Spatial Smoothing ◽  
Music Algorithm ◽  
Signal Model ◽  
Simulation Results

This paper presents a beamforming matrix with spatial smoothing effect, and extends it to the space-time 2D signal model, which not only reduces the computational complexity of the space-time 2D MUSIC algorithm and improves the coherence resolution capacity, simulation results show that this algorithm has better performance and effectiveness than MUSIC itself.

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