scholarly journals A New Subcarrier Allocation Strategy for MIMO-OFDMA Multicellular Networks Based on Cooperative Interference Mitigation

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Panagiotis K. Gkonis ◽  
Maria A. Seimeni ◽  
Nikolaos P. Asimakis ◽  
Dimitra I. Kaklamani ◽  
Iakovos S. Venieris
Keyword(s):  
Multiple Access ◽  
Interference Mitigation ◽  
Traditional Approach ◽  
Multiple Input Multiple Output ◽  
Central Cell ◽  
Subcarrier Allocation ◽  
Allocation Strategy ◽  
Multiple Input ◽  
Qam Modulation ◽  
Input Multiple Output

The goal of the study presented in this paper is to investigate the performance of a new subcarrier allocation strategy for Orthogonal Frequency Division Multiple Access (OFDMA) multicellular networks which employ Multiple Input Multiple Output (MIMO) architecture. For this reason, a hybrid system-link level simulator has been developed executing independent Monte Carlo (MC) simulations in parallel. Up to two tiers of cells around the central cell are taken into consideration and increased loading per cell. The derived results indicate that this strategy can provide up to 12% capacity gain for 16-QAM modulation and two tiers of cells around the central cell in a symmetric2×2MIMO configuration. This gain is derived when comparing the proposed strategy to the traditional approach of allocating subcarriers that maximize only the desired user’s signal.

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>

Lattice Reduction Algorithm Based Uplink MC-CDMA

2015 ◽  
Vol 738-739 ◽  
pp. 391-396
Author(s):  
Umut Yunus ◽  
Askar Hamdulla ◽  
Zhen Hong Jia ◽  
Kurban Ubul
Keyword(s):  
Communication Systems ◽  
Multiple Access ◽  
Multiple Input Multiple Output ◽  
Lattice Reduction ◽  
Rate Performance ◽  
Multiple Input ◽  
High Spectral Efficiency ◽  
Input Multiple Output ◽  
Cdma Systems ◽  
Multi Access

MC-CDMA integrates the advantages of OFDM with those of CDMA, it has high spectral efficiency, robustness against multi-path propagation and multiple access flexibility. Due to the above mentioned merits, it has been considered as a candidate for future wireless. In recent years, lattice reduction technique is discussed in multiple input multiple output communication systems, and has been shown with its better performance. The purpose of this paper is to express a model for uplink MC-CDMA systems in matrix form and then to propose a lattice reduction aided multiuser detection, in order to ameliorate the affects of inter-carrier interference and multi access interference. The effectiveness of the proposed method is evaluated by the bit error rate performance.

scholarly journals Downlink Multiuser Hybrid Beamforming for MmWave Massive MIMO-NOMA System with Imperfect CSI

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Jing Jiang ◽  
Ming Lei ◽  
Huanhuan Hou
Keyword(s):  
Multiple Access ◽  
Multiple Input Multiple Output ◽  
Digital Beamforming ◽  
Cluster Set ◽  
Power Difference ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Hybrid Beamforming ◽  
Rate Requirement ◽  
Effective Channel

This paper aims to provide a comprehensive scheme with limited feedback for downlink millimeter wave (mmWave) multiuser multiple-input multiple-output (MIMO) nonorthogonal multiple access (NOMA) system. Based on the feedback of the best beam and the channel quality information (CQI) on this beam, the users are grouped into a cluster having the same or coherent best beam and the maximal CQI-difference. To further reduce the intercluster interference, only the candidate cluster can join the cluster set whose intercluster correlation with the existing clusters is lower than threshold. Based on the results of clustering, mmWave hybrid beamforming is designed. To improve the user experience, each cluster selects the best beam of the user with the higher guaranteed rate requirement as the analog beamforming vector. For digital beamforming, the weak user applies the block diagonalization algorithm based on the strong user’s effective channel to reduce its intracluster interference. Finally, an intracluster power allocation algorithm is developed to maximize the power difference in each cluster which is beneficial to improve the successive interference cancelation (SIC) performance of the strong user. Finally, simulation results show that the proposed MIMO-NOMA scheme offers a higher sum rate than the traditional orthogonal multiple access (OMA) scheme under practical conditions.

Investigation of the fifth generation non-orthogonal multiple access technique for defense applications using deep learning

2021 ◽  
pp. 154851292110228
Author(s):  
Ravisankar Malladi ◽  
Manoj Kumar Beuria ◽  
Ravi Shankar ◽  
Sudhansu Sekhar Singh
Keyword(s):  
Deep Learning ◽  
Interference Cancellation ◽  
Multiple Access ◽  
Multiple Input Multiple Output ◽  
Optimal Solution ◽  
Channel State ◽  
Fifth Generation ◽  
Multiple Input ◽  
Input Multiple Output ◽  
And Performance

In modern wireless communication scenarios, non-orthogonal multiple access (NOMA) provides high throughput and spectral efficiency for fifth generation (5G) and beyond 5G systems. Traditional NOMA detectors are based on successive interference cancellation (SIC) techniques at both uplink and downlink NOMA transmissions. However, due to imperfect SIC, these detectors are not suitable for defense applications. In this paper, we investigate the 5G multiple-input multiple-output NOMA deep learning technique for defense applications and proposed a learning approach that investigates the communication system’s channel state information automatically and identifies the initial transmission sequences. With the use of the proposed deep neural network, the optimal solution is provided, and performance is much better than the traditional SIC-based NOMA detectors. Through simulations, the analytical outcomes are verified.

scholarly journals SCMA-MIMO system with adaptation to the channel state

2021 ◽  
Vol 2134 (1) ◽  
pp. 012025
Author(s):  
Dmitriy Pokamestov ◽  
Yakov Kryukov ◽  
Eugeniy Rogozhnikov ◽  
Islam Kanatbekuli ◽  
Edgar Dmitriyev
Keyword(s):  
Communication System ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Access ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Network Resources ◽  
Multiple Input ◽  
The Matrix ◽  
High Spectral Efficiency ◽  
Input Multiple Output

Abstract Sparse code multiple access (SCMA) is one of the promising implementations of non-orthogonal multiple access (NOMA) methods. SCMA provides high spectral efficiency and a large number of network resources. We describe a communication system with SCMA, space-time block coding (STBC), multiple input multiple output (MIMO) technology, and orthogonal frequency division multiplexing (OFDM). The architecture of such systems, including algorithms of formation and processing of signals is considered. A method for adapting signals to the state of the spatial channel transmission based on information about the matrix of channel coefficients is proposed. The application of such adaptation allows to compensate the influence of the channel and to reduce the probability of bit errors. We consider the bit error rate (BER) performance of the communication system in different channel models and show the effectiveness of the proposed methods.

scholarly journals A Deep Neural Network-Based Interference Mitigation for MIMO-FBMC/OQAM Systems

2021 ◽  
Vol 2 ◽  
Author(s):  
Abla Bedoui ◽  
Mohamed Et-tolba
Keyword(s):  
Neural Network ◽  
Communication Systems ◽  
Deep Neural Network ◽  
Interference Mitigation ◽  
Multiple Input Multiple Output ◽  
Filter Bank Multicarrier ◽  
Multiple Input ◽  
High Spectral Efficiency ◽  
Input Multiple Output ◽  
Imaginary Field

Offset quadrature amplitude modulation-based filter bank multicarrier (FBMC/OQAM) is among the promising waveforms for future wireless communication systems. This is due to its flexible spectrum usage and high spectral efficiency compared with the conventional multicarrier schemes. However, with OQAM modulation, the FBMC/OQAM signals are not orthogonal in the imaginary field. This causes a significant intrinsic interference, which is an obstacle to apply multiple input multiple output (MIMO) technology with FBMC/OQAM. In this paper, we propose a deep neural network (DNN)-based approach to deal with the imaginary interference, and enable the application of MIMO technique with FBMC/OQAM. We show, by simulations, that the proposed approach provides good performance in terms of bit error rate (BER).

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