scholarly journals Reduced Complexity Tree Search Algorithms for MIMO Decoding

2015 ◽  
Vol 10 (4) ◽  
pp. 230
Author(s):  
Gajanan R Patil ◽  
Vishwanath K Kokate
Keyword(s):  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Search Algorithms ◽  
Error Rates ◽  
Sphere Decoding ◽  
Current Layer ◽  
Tree Search ◽  
Maximum Likelihood Decoding ◽  
Initial Radius ◽  
Input Multiple Output

Maximum Likelihood Decoding (MLD) is computationally complex technique for decoding received information in multiple input multiple output (MIMO) systems. Tree search algorithms such as sphere decoding (SD) and QR decomposition with M survivals (QRD-M) are used to reduce the complexity keeping the performance near ML. This paper presents two techniques for reducing the computational complexities of the tree search algorithms further. The first technique is based on selecting the initial radius for sphere decoding. The main contribution of this paper is that the greedy best first search is used to compute initial radius, instead of Babai estimate. The second contribution is, QRD-M algorithm is modified to prune the nodes in the current layer based on maximum metric of child nodes of smallest surviving node. The performance of the proposed techniques is tested for different MIMO systems in terms of bit error rates (BER) and average number of nodes visited. The proposed schemes have improved computational complexity with no degradation of performance.

scholarly journals Adaptive Threshold-Aided K-Best Sphere Decoding for Large MIMO Systems

2019 ◽  
Vol 9 (21) ◽  
pp. 4624
Author(s):  
Uzokboy Ummatov ◽  
Kyungchun Lee
Keyword(s):  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Threshold Value ◽  
Adaptive Threshold ◽  
Sphere Decoding ◽  
High Signal ◽  
Signal To Noise ◽  
Multiple Input ◽  
Input Multiple Output

This paper proposes an adaptive threshold-aided K-best sphere decoding (AKSD) algorithm for large multiple-input multiple-output systems. In the proposed scheme, to reduce the average number of visited nodes compared to the conventional K-best sphere decoding (KSD), the threshold for retaining the nodes is adaptively determined at each layer of the tree. Specifically, we calculate the adaptive threshold based on the signal-to-noise ratio and index of the layer. The ratio between the first and second smallest accumulated path metrics at each layer is also exploited to determine the threshold value. In each layer, in addition to the K paths associated with the smallest path metrics, we also retain the paths whose path metrics are within the threshold from the Kth smallest path metric. The simulation results show that the proposed AKSD provides nearly the same bit error rate performance as the conventional KSD scheme while achieving a significant reduction in the average number of visited nodes, especially at high signal-to-noise ratios.

scholarly journals Fully Pipelined Implementation of Tree-Search Algorithms for Vector Precoding

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Maitane Barrenechea ◽  
Mikel Mendicute ◽  
Egoitz Arruti
Keyword(s):  
Data Processing ◽  
Hardware Implementation ◽  
Multiple Input Multiple Output ◽  
Search Algorithms ◽  
Search Problem ◽  
Tree Search ◽  
High Data ◽  
Field Programmable ◽  
Input Multiple Output ◽  
Downlink Channels

The nonlinear vector precoding (VP) technique has been proven to achieve close-to-capacity performance in multiuser multiple-input multiple-output (MIMO) downlink channels. The performance benefit with respect to its linear counterparts stems from the incorporation of a perturbation signal that reduces the power of the precoded signal. The computation of this perturbation element, which is known to belong in the class of NP-hard problems, is the main aspect that hinders the hardware implementation of VP systems. To this respect, several tree-search algorithms have been proposed for the closest-point lattice search problem in VP systems hitherto. Nevertheless, the optimality of these algorithms has been assessed mainly in terms of error-rate performance and computational complexity, leaving the hardware cost of their implementation an open issue. The parallel data-processing capabilities of field-programmable gate arrays (FPGA) and the loopless nature of the proposed tree-search algorithms have enabled an efficient hardware implementation of a VP system that provides a very high data-processing throughput.

scholarly journals Low-complexity sparse-aware multiuser detection for large-scale MIMO systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Rong Ran ◽  
Hayoung Oh
Keyword(s):  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Finite Alphabet ◽  
Multiuser Detectors ◽  
Input Multiple Output ◽  
Error Detector ◽  
Significant Performance

AbstractSparse-aware (SA) detectors have attracted a lot attention due to its significant performance and low-complexity, in particular for large-scale multiple-input multiple-output (MIMO) systems. Similar to the conventional multiuser detectors, the nonlinear or compressive sensing based SA detectors provide the better performance but are not appropriate for the overdetermined multiuser MIMO systems in sense of power and time consumption. The linear SA detector provides a more elegant tradeoff between performance and complexity compared to the nonlinear ones. However, the major limitation of the linear SA detector is that, as the zero-forcing or minimum mean square error detector, it was derived by relaxing the finite-alphabet constraints, and therefore its performance is still sub-optimal. In this paper, we propose a novel SA detector, named single-dimensional search-based SA (SDSB-SA) detector, for overdetermined uplink MIMO systems. The proposed SDSB-SA detector adheres to the finite-alphabet constraints so that it outperforms the conventional linear SA detector, in particular, in high SNR regime. Meanwhile, the proposed detector follows a single-dimensional search manner, so it has a very low computational complexity which is feasible for light-ware Internet of Thing devices for ultra-reliable low-latency communication. Numerical results show that the the proposed SDSB-SA detector provides a relatively better tradeoff between the performance and complexity compared with several existing detectors.

PROBLEM STATEMENT OF JOINT ANTENNA SELECTION AND PRECODING IN MASSIVE MIMO COMMUNICATION SYSTEMS

2021 ◽  
Author(s):  
В.Б. КРЕЙНДЕЛИН ◽  
М.В. ГОЛУБЕВ
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Research Areas ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Legal Restrictions ◽  
Multiple Transmission

Совместный с прекодингом автовыбор антенн на приемной и передающей стороне - одно из перспективных направлений исследований для реализации технологий Multiple Transmission and Reception Points (Multi-TRP, множество точек передачи и приема) в системах со многими передающими и приемными антеннами Massive MIMO (Multiple-Input-Multiple-Output), которые активно развиваются в стандарте 5G. Проанализированы законодательные ограничения, влияющие на применимость технологий Massive MIMO, и специфика реализации разрабатываемого алгоритма в миллиметровомдиапа -зоне длин волн. Рассмотрены алгоритмы формирования матриц автовыбора антенн как на передающей, так и на приемной стороне. Сформулирована строгая математическая постановка задачи для двух критериев работы алгоритма: максимизация взаимной информации и минимизация среднеквадратичной ошибки. Joint precoding and antenna selection both on transmitter and receiver sides is one of the promising research areas for evolving toward the Multiple Transmission and Reception Points (Multi-TRP) concept in Massive MIMO systems. This technology is under active development in the coming 5G 3GPP releases. We analyze legal restrictions for the implementation of 5G Massive MIMO technologies in Russia and the specifics of the implementation of the developed algorithm in the millimeter wavelength range. Algorithms of antenna auto-selection matrices formation on both transmitting and receiving sides are considered. Two criteria are used for joint antenna selection and precoding: maximizing mutual information and minimizing mean square error.

scholarly journals MIMO Self-Encoded Spread Spectrum with Iterative Detection over Rayleigh Fading Channels

2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
Shichuan Ma ◽  
Lim Nguyen ◽  
Won Mee Jang ◽  
Yaoqing (Lamar) Yang
Keyword(s):  
Fading Channels ◽  
Spread Spectrum ◽  
Rayleigh Fading ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Spatial Diversity ◽  
Iterative Detection ◽  
Channel Fading ◽  
Input Multiple Output

Self-encoded spread spectrum (SESS) is a novel communication technique that derives its spreading code from the randomness of the source stream rather than using conventional pseudorandom noise (PN) code. In this paper, we propose to incorporate SESS in multiple-input multiple-output (MIMO) systems as a means to combat against fading effects in wireless channels. Orthogonal space-time block-coded MIMO technique is employed to achieve spatial diversity, and the inherent temporal diversity in SESS modulation is exploited with iterative detection. Simulation results demonstrate that MIMO-SESS can effectively mitigate the channel fading effect such that the system can achieve a bit error rate of with very low signal-to-noise ratio, from 3.3 dB for a antenna configuration to just less than 0 dB for a configuration under Rayleigh fading. The performance improvement for the case is as much as 6.7 dB when compared to an MIMO PN-coded spread spectrum system.

scholarly journals Location-Aided Uplink Transmission for User-Centric Cell-Free Massive MIMO Systems: A Fairness Priority Perspective

2022 ◽  
Author(s):  
Chen Wei ◽  
Kui Xu ◽  
Zhexian Shen ◽  
Xiaochen Xia ◽  
Wei Xie ◽  
...  
Keyword(s):  
Large Scale ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Access Point ◽  
Estimation Accuracy ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output ◽  
User Centric ◽  
Assignment Scheme

Abstract In this paper, we investigate the uplink transmission for user-centric cell-free massive multiple-input multiple-output (MIMO) systems. The largest-large-scale-fading-based access point (AP) selection method is adopted to achieve a user-centric operation. Under this user-centric framework, we propose a novel inter-cluster interference-based (IC-IB) pilot assignment scheme to alleviate pilot contamination. Considering the local characteristics of channel estimates and statistics, we propose a location-aided distributed uplink combining scheme based on a novel proposed metric representing inter-user interference to balance the relationship among the spectral efficiency (SE), user equipment (UE) fairness and complexity, in which the normalized local partial minimum mean-squared error (LP-MMSE) combining is adopted for some APs, while the normalized maximum ratio (MR) combining is adopted for the remaining APs. A new closed-form SE expression using the normalized MR combining is derived and a novel metric to indicate the UE fairness is also proposed. Moreover, the max-min fairness (MMF) power control algorithm is utilized to further ensure uniformly good service to the UEs. Simulation results demonstrate that the channel estimation accuracy of our proposed IC-IB pilot assignment scheme outperforms that of the conventional pilot assignment schemes. Furthermore, although the proposed location-aided uplink combining scheme is not always the best in terms of the per-UE SE, it can provide the more fairness among UEs and can achieve a good trade-off between the average SE and computational complexity.

scholarly journals The Downlink Performance for Cell-Free Massive MIMO with Instantaneous CSI in Slowly Time-Varying Channels

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1552
Author(s):  
Tongzhou Han ◽  
Danfeng Zhao
Keyword(s):  
Power Control ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Time Varying ◽  
Input Multiple Output ◽  
Efficiency Performance ◽  
A Cell ◽  
Time Varying Channel

In centralized massive multiple-input multiple-output (MIMO) systems, the channel hardening phenomenon can occur, in which the channel behaves as almost fully deterministic as the number of antennas increases. Nevertheless, in a cell-free massive MIMO system, the channel is less deterministic. In this paper, we propose using instantaneous channel state information (CSI) instead of statistical CSI to obtain the power control coefficient in cell-free massive MIMO. Access points (APs) and user equipment (UE) have sufficient time to obtain instantaneous CSI in a slowly time-varying channel environment. We derive the achievable downlink rate under instantaneous CSI for frequency division duplex (FDD) cell-free massive MIMO systems and apply the results to the power control coefficients. For FDD systems, quantized channel coefficients are proposed to reduce feedback overhead. The simulation results show that the spectral efficiency performance when using instantaneous CSI is approximately three times higher than that achieved using statistical CSI.

scholarly journals Beam division multiple access for millimeter wave massive MIMO: Hybrid zero-forcing beamforming with user selection

2022 ◽  
Vol 12 (1) ◽  
pp. 445
Author(s):  
Hong Son Vu ◽  
Kien Truong ◽  
Minh Thuy Le
Keyword(s):  
Multiple Access ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Zero Forcing ◽  
Multiuser Interference ◽  
Novel Approach ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Promising Solution

<p>Massive multiple-input multiple-output (MIMO) systems are considered a promising solution to minimize multiuser interference (MUI) based on simple precoding techniques with a massive antenna array at a base station (BS). This paper presents a novel approach of beam division multiple access (BDMA) which BS transmit signals to multiusers at the same time via different beams based on hybrid beamforming and user-beam schedule. With the selection of users whose steering vectors are orthogonal to each other, interference between users is significantly improved. While, the efficiency spectrum of proposed scheme reaches to the performance of fully digital solutions, the multiuser interference is considerably reduced.</p>

Quantum algorithm for MUSIC-based DOA estimation in hybrid MIMO systems

2021 ◽  
Author(s):  
Fan-Xu Meng ◽  
Ze-Tong Li ◽  
Xutao Yu ◽  
Zaichen Zhang
Keyword(s):  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Quantum Algorithm ◽  
Doa Estimation ◽  
Quantum Circuit ◽  
Music Algorithm ◽  
Quantum Method ◽  
Sample Covariance ◽  
Input Multiple Output ◽  
Eigen Decomposition

Abstract The multiple signal classification (MUSIC) algorithm is a well-established method to evaluate the direction of arrival (DOA) of signals. However, the construction and eigen-decomposition of the sample covariance matrix (SCM) are computationally costly for MUSIC in hybrid multiple input multiple output (MIMO) systems, which limits the application and advancement of the algorithm. In this paper, we present a novel quantum method for MUSIC in hybrid MIMO systems. Our scheme makes the following three contributions. First, the quantum subroutine for constructing the approximate SCM is designed, along with the quantum circuit for the steering vector and a proposal for quantum singular vector transformation. Second, the variational density matrix eigensolver is proposed to determine the signal and noise subspaces utilizing the destructive swap test. As a proof of principle, we conduct two numerical experiments using a quantum simulator. Finally, the quantum labelling procedure is explored to determine the DOA. The proposed quantum method can potentially achieve exponential speedup on certain parameters and polynomial speedup on others under specific moderate circumstances, compared with their classical counterparts.

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