Coordinated Precoding for D2D Communications Underlay Uplink MIMO Cellular Networks

We study the coordinated precoding problem for device-to-device (D2D) communications underlay multiple-input multiple-output (MIMO) cellular networks. The system model considered here constitutes multiple D2D user pairs attempting to share the uplink radio resources of a cellular network. We first formulate the coordinated precoding problem for the D2D user pairs as a sum-rate maximization (SRM) problem, which is subject to a total interference power constraint imposed to protect the base station (BS) and individual transmit power budgets available for each D2D user pair. Since the formulated SRM problem is nonconvex in general, we reformulate it as a difference convex- (DC-) type programming problem, which can be iteratively solved by employing the famous successive convex approximation (SCA) method. Moreover, a proximal-point-based regularization approach is also pursued here to ensure the convergence of the proposed algorithm. Interestingly, the centralized precoding algorithm can also lend itself to a distributed implementation. By introducing a price-based interference management mechanism, we reformulate the coordinated precoding problem as a Stackelberg game. Then, a distributed precoding algorithm is developed based on the concept of Stackelberg equilibrium (SE). Finally, numerical simulations are also provided to demonstrate the proposed algorithms. Results show that our algorithms can converge fast to a satisfactory solution with guaranteed convergence.

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Incentive and Penalty Mechanism for Power Allocation in Cooperative D2D-Cellular Transmissions

Electronics ◽

10.3390/electronics9030408 ◽

2020 ◽

Vol 9 (3) ◽

pp. 408

Author(s):

Shama Noreen ◽

Navrati Saxena ◽

Abhishek Roy

Keyword(s):

Communication Systems ◽

Stackelberg Game ◽

Dead Zone ◽

Interference Management ◽

Base Station ◽

D2d Communications ◽

High Data ◽

Reasonable Solution ◽

Joint Pricing

In cellular communication systems, the introduction of device-to-device (D2D) communications provides a reasonable solution to facilitate high data rate services in short-range communication. However, it faces a challenging issue of interference management, where the cross-tier interference from D2D users to licensed cellular users (CUs) degrades their quality-of-service (QoS) requirements. D2D communications can also assist in offloading some nearby CUs to enhance the cellular operator’s benefit. To encourage the D2D transmitters (D2DT) to provide service to CUs in the dead zone, the cellular base station (CBS) needs to incentivize it with some monetary benefits. In this paper, a Stackelberg game-based joint pricing framework for interference management and data offloading is presented to illustrate the effects of cooperation between the D2D user and CBS. Specifically, a singular price is used to incentivize the D2DT to share its resources with the far-off CUs along with penalizing them for interference created at CBS. Simulation results illustrate the performance of the proposed technique in terms of the utilities of CUs and D2D users for varying distances of D2DT.

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Implementation of a Zero-Forcing Precoding Algorithm Combined with Adaptive Beamforming Based on WiMAX System

International Journal of Antennas and Propagation ◽

10.1155/2013/976301 ◽

2013 ◽

Vol 2013 ◽

pp. 1-7 ◽

Cited By ~ 1

Author(s):

Hyunwook Yang ◽

Seungwon Choi

Keyword(s):

Mimo System ◽

Multiple Input Multiple Output ◽

Experimental System ◽

Multiple Access Interference ◽

Adaptive Beamforming ◽

Base Station ◽

Zero Forcing ◽

Single Antenna ◽

Input Multiple Output ◽

Wimax System

We propose a novel precoding algorithm that is a zero-forcing (ZF) method combined with adaptive beamforming in the Worldwide Interoperability for Microwave Access (WiMAX) system. In a Multiuser Multiple-Input Multiple-Output (MU-MIMO) system, ZF is used to eliminate the Multiple Access Interference (MAI) in order to allow several users to share a common resource. The adaptive beamforming algorithm is used to achieve the desired SNR gain. The experimental system consists of a WiMAX base station that has 2 MIMO elements, each of which is composed of three-array antennas and two mobile terminals, each of which has a single antenna. Through computer simulations, we verified that the proposed method outperforms the conventional ZF method by at least 2.4 dB when the BER is 0.1%, or 1.7 dB when the FER is 1%, in terms of the SNR. Through a hardware implementation of the proposed method, we verified the feasibility of the proposed method for realizing a practical WiMAX base station to utilize the channel resources as efficiently as possible.

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Study of 5G-NR-MIMO Links in the Presence of an Interferer

Electronics ◽

10.3390/electronics10060732 ◽

2021 ◽

Vol 10 (6) ◽

pp. 732

Author(s):

Avner Elgam ◽

Yael Balal ◽

Yosef Pinhasi

Keyword(s):

Mobile Networks ◽

Communication Systems ◽

Multiple Input Multiple Output ◽

Local Area ◽

Maximum Energy ◽

Base Station ◽

Small Cells ◽

Diversity Coding ◽

Shift Keying ◽

Input Multiple Output

Many communication systems are based on the Multiple Input, Multiple Output (MIMO) scheme, and Orthogonal Space–time Block Transmit diversity Coding (OSTBC), combined with Maximal Ratio Receive Combining (MRRC), to create an optimal diversity system. A system with optimal diversity fixes and optimizes the channel’s effects under multi-path and Rayleigh fading with maximum energy efficiency; however, the challenge does not end with dealing with the channel destruction of the multi-path impacts. Susceptibility to interference is a significant vulnerability in future wireless mobile networks. The 5th Generation New Radio (5G-NR) technologies bring hundreds of small cells and pieces of User Equipment (UE) per indoor or outdoor local area scenario under a specific Long Term Evolution (LTE)-based station (e-NodeB), or under 5G-NR base-station (g-NodeB). It is necessary to study issues that deal with many interference signals, and smart jammers from advanced communication equipment cause deterioration in the links between the UE, the small cells, and the NodeB. In this paper, we study and present the significant impact and performances of 2×2 Alamouti Phase-Shift Keying (PSK) modulation techniques in the presence of an interferer and a smart jammer. The destructive effects affecting the MIMO array and the advanced diversity technique without closed-loop MIMO are analyzed. The performance is evaluated in terms of Bit Error Rate (BER) vs. Signal to Interference Ratio (SIR). In addition, we proved the impairment of the orthogonal spectrum assumption mathematically.

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A companding approach for PAPR suppression in OFDM based massive MIMO system

Journal of Optical Communications ◽

10.1515/joc-2020-0255 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Ajay Kumar Yadav ◽

Pritam Keshari Sahoo ◽

Yogendra Kumar Prajapati

Keyword(s):

Massive Mimo ◽

Orthogonal Frequency Division Multiplexing ◽

Mimo System ◽

Multiple Input Multiple Output ◽

Average Power ◽

Base Station ◽

Convex Optimization Problem ◽

Multiple Input ◽

Input Multiple Output ◽

Mimo Ofdm

Abstract Orthogonal frequency division multiplexing (OFDM) based massive multiuser (MU) multiple input multiple output (MIMO) system is popularly known as high peak-to-average power ratio (PAPR) issue. The OFDM-based massive MIMO system exhibits large number of antennas at Base Station (BS) due to the use of large number of high-power amplifiers (HPA). High PAPR causes HPAs to work in a nonlinear region, and hardware cost of nonlinear HPAs are very high and also power inefficient. Hence, to tackle this problem, this manuscript suggests a novel scheme based on the joint MU precoding and PAPR minimization (PP) expressed as a convex optimization problem solved by steepest gradient descent (GD) with μ-law companding approach. Therefore, we develop a new scheme mentioned to as MU-PP-GDs with μ-law companding to minimize PAPR by compressing and enlarging of massive MIMO OFDM signals simultaneously. At CCDF = 10−3, the proposed scheme (MU-PP-GDs with μ-law companding for Iterations = 100) minimizes the PAPR to 3.70 dB which is better than that of MU-PP-GDs, (iteration = 100) as shown in simulation results.

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Interference management for D2D communications in heterogeneous cellular networks

Pervasive and Mobile Computing ◽

10.1016/j.pmcj.2018.10.005 ◽

2018 ◽

Vol 51 ◽

pp. 138-149 ◽

Cited By ~ 4

Author(s):

Yanli Xu ◽

Feng Liu ◽

Ping Wu

Keyword(s):

Cellular Networks ◽

Interference Management ◽

D2d Communications ◽

Heterogeneous Cellular Networks

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

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v12i1.pp445-452 ◽

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>

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High gain 5G MIMO antenna for mobile base station

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v9i1.pp468-476 ◽

2019 ◽

Vol 9 (1) ◽

pp. 468 ◽

Cited By ~ 2

Author(s):

Yusnita Rahayu ◽

Indah Permata Sari ◽

Dara Incam Ramadhan ◽

Razali Ngah

Keyword(s):

Linear Array ◽

Multiple Input Multiple Output ◽

High Gain ◽

Base Station ◽

Impedance Bandwidth ◽

Single Element ◽

Mimo Antenna ◽

Input Multiple Output ◽

Mobile Base Station ◽

Mobile Base

This article presented a millimeter wave antenna which operated at 38 GHz for 5G mobile base station. The MIMO (Multiple Input Multiple Output) antenna consisted of 1x10 linear array configurations. The proposed antenna’s size was 88 x 98 mm^2 and printed on 1.575 mm-thick Rogers Duroid 5880 subsrate with dielectric constant of ε_r= 2.2 and loss tangent (tanδ) of 0.0009. The antenna array covered along the azimuth plane to provide the coverage to the users in omnidirection. The simulated results showed that the single element antenna had the reflection coefficient (S11) of -59 dB, less than -10 dB in the frequency range of 35.5 - 39.6 GHz. More than 4.1 GHz of impedance bandwidth was obtained. The gain of the antenna linear array was 17.8 dBi while the suppression of the side lobes was -2.7 dB. It showed a high array gain throughout the impedance bandwidth with overall of VSWR were below 1.0646. It designed using CST microwave studio.

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

Electronics ◽

10.3390/electronics9111844 ◽

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.

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