scholarly journals A dynamic Q-learning beamforming method for inter-cell interference mitigation in 5G massive MIMO networks

2021 ◽  
Vol 2 (4) ◽  
pp. 47-55
Author(s):  
Aidong Yang ◽  
Xinlang Yue ◽  
Mohan Wu ◽  
Ye Ouyang
Keyword(s):  
Interference Mitigation ◽  
Multiple Input Multiple Output ◽  
Service Improvement ◽  
Q Learning ◽  
Mimo Networks ◽  
Channel Knowledge ◽  
Input Multiple Output ◽  
Efficiency Performance ◽  
Channel Information ◽  
Inter Cell Interference

Beamforming is an essential technology in 5G Massive Multiple-Input Multiple-Output (MMIMO) communications, which are subject to many impairments due to the nature of wireless transmission channel. The Inter-Cell Interference (ICI) is one of the main obstacles faced by 5G communications due to frequency-reuse technologies. However, finding the optimal beamforming parameter to minimize the ICI requires infeasible prior network or channel information. In this paper, we propose a dynamic Q-learning beamforming method for ICI mitigation in the 5G downlink that does not require prior network or channel knowledge. Compared with a traditional beamforming method and other industrial Reinforcement Learning (RL) methods, the proposed method has lower computational complexity and better convergence efficiency. Performance analysis shows the quality of service improvement in terms of Signal-to-Interference-plus-Noise-Ratio (SINR) and the robustness towards different environments.

Performance evaluation of inter-cell interference prediction in massive MIMO

2021 ◽  
Vol 3 (1) ◽  
pp. 28-36
Author(s):  
Abayomi Isiaka O. Yussuff ◽  
◽  
Abdul-Rasaq A. Bakare ◽  
Keyword(s):  
Coverage Probability ◽  
Interference Mitigation ◽  
Performance Metrics ◽  
Multiple Input Multiple Output ◽  
Prediction Scheme ◽  
5G Network ◽  
Multiple Input ◽  
Input Multiple Output ◽  
The Moment ◽  
Inter Cell Interference

This paper presents inter-cell interference prediction in massive multiple input multiple output. The rapid demand for widespread multimedia services notwithstanding the deployment of 4G in Lagos, Nigeria and the urgent need to upgrade to 5G networks with downlink and uplink data capacities of not less than 300 and 60 Mbps, respectively for at least 95% penetration rate at any instantaneous time; there is a possibility of experiencing crosstalk and adjacent inter-cell interference within the receiving antennas. 5G inter-cell interference prediction scheme that employs LTE performance index using locally sourced data from Huawei Nigeria limited was presented. The performances of the currently deployed LTE network were evaluated by employing performance metrics such as uplink and downlink capacities and recommending a possible inter-cell interference mitigation technique to be implemented in the deployment of 5G network in Lagos. The identified key performance metrics used include over the air emulation, carrier to interference plus noise ratio, peak RLC throughput, coverage probability, and the map-based model. Hence, ICIC static coordination algorithm, which comprise NOICIC, Hard FFR, PFR, SFR and SFFR were analyzed. With static ICIC algorithm, the coverage probability was 78% for receiving more than 20 kbps, with cell-edge users using resources of centre-users and with edge-users of neighbouring cells using different resource block; therefore reducing interference and consequently increasing throughput when there is static ICIC coordination. Implementing the static ICIC schemes on the 5G network when deployed in Lagos will improve the average downlink throughput over what is currently attainable with the 4G network in use at the moment

scholarly journals Genetic Algorithm-Based Beam Refinement for Initial Access in Millimeter Wave Mobile Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Hao Guo ◽  
Behrooz Makki ◽  
Tommy Svensson
Keyword(s):  
Genetic Algorithm ◽  
Millimeter Wave ◽  
Mobile Networks ◽  
System Performance ◽  
Multiple Input Multiple Output ◽  
Hardware Impairments ◽  
Mimo Networks ◽  
Multiple Input ◽  
Input Multiple Output ◽  
High Carrier

Initial access (IA) is identified as a key challenge for the upcoming 5G mobile communication system operating at high carrier frequencies, and several techniques are currently being proposed. In this paper, we extend our previously proposed efficient genetic algorithm- (GA-) based beam refinement scheme to include beamforming at both the transmitter and the receiver and compare the performance with alternative approaches in the millimeter wave multiuser multiple-input-multiple-output (MU-MIMO) networks. Taking the millimeter wave communications characteristics and various metrics into account, we investigate the effect of different parameters such as the number of transmit antennas/users/per-user receive antennas, beamforming resolutions, and hardware impairments on the system performance employing different beam refinement algorithms. As shown, our proposed GA-based approach performs well in delay-constrained networks with multiantenna users. Compared to the considered state-of-the-art schemes, our method reaches the highest service outage-constrained end-to-end throughput with considerably less implementation complexity. Moreover, taking the users’ mobility into account, our GA-based approach can remarkably reduce the beam refinement delay at low/moderate speeds when the spatial correlation is taken into account. Finally, we compare the cases of collaborative users and noncollaborative users and evaluate their difference in system performance.

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 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 Deep Scanning—Beam Selection Based on Deep Reinforcement Learning in Massive MIMO Wireless Communication System

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1844
Author(s):  
Minhoe Kim ◽  
Woongsup Lee ◽  
Dong-Ho Cho
Keyword(s):  
Communication Systems ◽  
Large Scale ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Q Learning ◽  
Multiple Input ◽  
Beam Selection ◽  
Input Multiple Output ◽  
Optimal Beam ◽  
Resource Allocation Scheme

In this paper, we investigate a deep learning based resource allocation scheme for massive multiple-input-multiple-output (MIMO) communication systems, where a base station (BS) with a large scale antenna array communicates with a user equipment (UE) using beamforming. In particular, we propose Deep Scanning, in which a near-optimal beamforming vector can be found based on deep Q-learning. Through simulations, we confirm that the optimal beam vector can be found with a high probability. We also show that the complexity required to find the optimum beam vector can be reduced significantly in comparison with conventional beam search schemes.

scholarly journals Decentralized Limited-Feedback Multiuser MIMO for Temporally Correlated Channels

2010 ◽  
Vol 2010 ◽  
pp. 1-9
Author(s):  
Eduardo Zacarías B ◽  
Stefan Werner ◽  
Risto Wichman
Keyword(s):  
Multiple Input Multiple Output ◽  
Limited Feedback ◽  
Mimo Channels ◽  
Linear Filters ◽  
Correlated Channels ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Channel Information ◽  
Feedback Algorithm ◽  
Temporally Correlated

This paper proposes a novel multiuser (MU) multiplexing scheme for temporally correlated multiple-input, multiple-output (MIMO) channels, suitable for systems employing low-rate feedback links. A decentralized solution is obtained by the mobile receivers, which employ interference rejection combiner (IRC) linear filters and command the update of the corresponding per-user antenna transmit weights through compact feedback messages, thus avoiding explicit transmission of channel information. The proposed limited-feedback algorithm outperforms existing MU-MIMO solutions employing quantized matrices, operating at the same feedback overhead. A compensation mechanism is presented, which enables the proposed solution to operate under moderate probabilities of feedback errors, at the expense of a small downlink overhead.

scholarly journals Precoding Designs for Full-Duplex Multi-User MIMO Cognitive Networks with Imperfect CSI

2019 ◽  
Vol 9 (1-2) ◽  
Author(s):  
Xuan-Xinh Nguyen ◽  
Ha Hoang Kha
Keyword(s):  
Objective Function ◽  
Multiple Input Multiple Output ◽  
Cognitive Networks ◽  
Full Duplex ◽  
Linear Matrix ◽  
Interference Constraints ◽  
Input Multiple Output ◽  
Efficiency Performance ◽  
Sum Rate ◽  
The Difference

This paper studies a cognitive radio (CR) network which consists of a full-duplex (FD) multi-user (MU) multiple-input multiple-output (MIMO) secondary user (SU) networks operating within the coverage of multiple primary users (PUs). It is assumed that the channel state information (CSI) matrices associated with SU systems are perfectly known whereas the CSI ones from SUs to PUs are imperfectly estimated. The problem of interest is to design robust precoding matrices at the SUs to maximize the CR sum rate subject to the SU transmit power constraints and harmful interference restrictions at PUs. Due to non-concavity of the objective function and intractability of robust PU interference constraints, the design problem is non-convex and challenging to directly solve. We exploit the difference of two concave functions to recast the sum rate objective function as a lower bounded concave one. In addition, a linear matrix inequality (LMI) transformation is used to handle the semi-infinite robust interference constraints. Then, the sequential convex programming method is carried out to iteratively solve a convex optimization problem in each iteration. The simulation results are provided to investigate the CR sum-rate (spectral efficiency) performance and the robustness against the CSI uncertainty.

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).

Analysis of Distributed MIMO Systems in a Multi-Cell Environment

2014 ◽  
Vol 696 ◽  
pp. 183-190
Author(s):  
Yue Heng Li ◽  
Ming Hao Fu ◽  
Li Wang ◽  
Mei Yan Ju ◽  
Ping Huang
Keyword(s):  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Research Work ◽  
Network Scheduling ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Communication Scheme ◽  
Inter Cell Interference ◽  
Output Sinr ◽  
Probability Density Function Pdf

This paper focuses its research work on the capacity and outage performances of a distributed multiple-input multiple-output (DMIMO) system in a multi-cell environment. For this purpose, the multi-cell DMIMO structure is modeled first, and based on this model, the so-called blanket communication and selective communication schemes are compared, and the formula of the output signal to interference plus noise ratio (SINR) of the above two schemes are given to illustrate the way of an inter-cell interference affecting the system performance. Then the expressions of the average capacity and outage probability are derived by using the probability density function (PDF) of the output SINR in the preferred selective communication scheme with some necessary approximations. Finally, the computer simulations are provided to explore the possible rule of upper layer network scheduling in overcoming the inter-cell interferences and in optimizing the capacity and outage performances in the DMIMO systems.

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