scholarly journals Utility-Based Wireless Routing Algorithm for Massive MIMO Heterogeneous Networks

2020 ◽  
Vol 10 (20) ◽  
pp. 7261
Author(s):  
Wei Zhao ◽  
Wen-Hsing Kuo
Keyword(s):  
Heterogeneous Networks ◽  
Massive Mimo ◽  
Routing Algorithm ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Base Stations ◽  
Small Cells ◽  
Multihop Wireless ◽  
Wireless Backhaul ◽  
Input Multiple Output

With the development of 5G communication, massive multiple input multiple output (MIMO) technology is getting more and more attention. Massive MIMO uses a large amount of simultaneous transmitting and receiving antennas to reduce power consumption and raise the level of transmission quality. Meanwhile, the diversification of user equipment (UE) in the 5G environment also makes heterogeneous networks (HetNets) more prevalent. HetNets allow UE of different network standards to access small cells, while the base stations of small cells access a macro base station (BS) to form a multihop wireless heterogeneous backhaul network. However, how to effectively combine these two technologies by efficiently allocating the antennas of each BS during the route construction process of heterogeneous wireless backhaul networks is still an important issue that is yet to be solved. In this paper, we propose an algorithm called preallocated sequential routing (PSR). Based on the links’ channel conditions and the available antennas and location of BSs, it builds a wireless heterogeneous network backhaul topology and adjusts each link’s transmitting and receiving antennas to maximize total utility. Simulation results showed that the proposed algorithm significantly improved the overall utility and the utility of the outer area of heterogeneous networks.

scholarly journals Performance evaluation of wireless data traffic in Mm wave massive MIMO communication

2020 ◽  
Vol 20 (3) ◽  
pp. 1342
Author(s):  
Ahmed Thair Al-Heety ◽  
Mohammad Tariqul Islam ◽  
Ahmed Hashim Rashid ◽  
Hasanain N. Abd Ali ◽  
Ali Mohammed Fadil ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Network Capacity ◽  
System Capacity ◽  
Small Cells ◽  
Data Traffic ◽  
Wireless Data ◽  
Wireless Backhaul ◽  
Input Multiple Output

<span>Due to the evaluation of mobile devices and applications in the current decade, a new direction for wireless networks has emerged. The general consensus about the future 5G network is that the following should be taken into account; the purpose of thousand-fold system capacity, hundredfold energy efficiency, lower latency, and smooth connectivity. The massive multiple-input multiple-output (MIMO), as well as the Millimeter wave (mm Wave) have been considered in the ultra-dense cellular network (UDN), because they are viewed as the emergent solution for the next generations of communication. This article focuses on evaluating and discussing the performance of mm Wave massive MIMO for ultra-dense network, which is one of the major technologies for the 5G wireless network. More so, the energy efficiencies of two kinds of architectures for wireless backhaul networks were investigated and compared in this article. The results of the simulation revealed some points that should be considered during the deployment of small cells in the two architectures UDN with backhaul network capacity and backhaul energy efficiency, that the changing the frequency bands in Distribution approach gives the same energy efficiency reached to 600 Mb/s at 15 nodes while the Conventional approach results reached less than 100 Mb/s at the same number of nodes.</span>

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

Electronics ◽  
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.

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

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.

scholarly journals Multi-Objective Optimization of Massive MIMO 5G Wireless Networks towards Power Consumption, Uplink and Downlink Exposure

2019 ◽  
Vol 9 (22) ◽  
pp. 4974 ◽  
Author(s):  
Michel Matalatala ◽  
Margot Deruyck ◽  
Sergei Shikhantsov ◽  
Emmeric Tanghe ◽  
David Plets ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Electric Field ◽  
Power Consumption ◽  
Massive Mimo ◽  
Rapid Development ◽  
Multiple Input Multiple Output ◽  
Base Stations ◽  
Reference Scenario ◽  
User Coverage ◽  
Input Multiple Output

The rapid development of the number of wireless broadband devices requires that the induced uplink exposure be addressed during the design of the future wireless networks, in addition to the downlink exposure due to the transmission of the base stations. In this paper, the positions and power levels of massive MIMO-LTE (Multiple Input Multiple Output-Long Term Evolution) base stations are optimized towards low power consumption, low downlink and uplink electromagnetic exposure and maximal user coverage. A suburban area in Ghent, Belgium has been considered. The results show that the higher the number of BS antenna elements, the fewer number of BSs the massive MIMO network requires. This leads to a decrease of the downlink exposure (−12% for the electric field and −32% for the downlink dose) and an increase of the uplink exposure (+70% for the uplink dose), whereas both downlink and uplink exposure increase with the number of simultaneous served users (+174% for the electric field and +22% for the uplink SAR). The optimal massive MIMO network presenting the better trade-off between the power consumption, the total dose and the user coverage has been obtained with 37 64-antenna BSs. Moreover, the level of the downlink electromagnetic exposure (electric field) of the massive MIMO network is 5 times lower than the 4G reference scenario.

scholarly journals A Survey on Massive MIMO Systems in Presence of Channel and Hardware Impairments

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 164 ◽  
Author(s):  
Zahra Mokhtari ◽  
Maryam Sabbaghian ◽  
Rui Dinis
Keyword(s):  
Massive Mimo ◽  
Orthogonal Frequency Division Multiplexing ◽  
Mimo Systems ◽  
Low Cost ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Aging Effects ◽  
Hardware Impairments ◽  
Single Carrier ◽  
Input Multiple Output

Massive multiple input multiple output (MIMO) technology is one of the promising technologies for fifth generation (5G) cellular communications. In this technology, each cell has a base station (BS) with a large number of antennas, allowing the simultaneous use of the same resources (e.g., frequency and/or time slots) by multiple users of a cell. Therefore, massive MIMO systems can bring very high spectral and power efficiencies. However, this technology faces some important issues that need to be addressed. One of these issues is the performance degradation due to hardware impairments, since low-cost RF chains need to be employed. Another issue is the channel estimation and channel aging effects, especially in fast mobility environments. In this paper we will perform a comprehensive study on these two issues considering two of the most promising candidate waveforms for massive MIMO systems: Orthogonal frequency division multiplexing (OFDM) and single-carrier frequency domain processing (SC-FDP). The studies and the results show that hardware impairments and inaccurate channel knowledge can degrade the performance of massive MIMO systems extensively. However, using suitable low complex estimation and compensation techniques and also selecting a suitable waveform can reduce these effects.

scholarly journals A Study of a Competitive Reinforcement Learning Approach for Joint Spatial Division and Multiplexing in Massive MIMO

2021 ◽  
Vol 19 (1) ◽  
pp. 83-93
Author(s):  
Tanyaluk Deeka ◽  
Boriboon Deeka ◽  
Surajate On-rit
Keyword(s):  
Massive Mimo ◽  
Energy Use ◽  
Multiple Input Multiple Output ◽  
Main Idea ◽  
Base Station ◽  
Machine Learning Algorithms ◽  
System Throughput ◽  
Computational Time ◽  
User Grouping ◽  
Input Multiple Output

Massive Multiple-Input Multiple-Output (MIMO) is widely considered a pivotal communication technology for future generations of wireless networks. Massive MIMO uses a large number of antennas at the base station, which offers better effectiveness in spectral and energy use. However, a Frequency Division Duplex (FDD) system is challenging in reciprocity since it is difficult to estimate channels and requires feeding back channel state information. Joint Spatial Division and Multiplexing (JSDM) is a simplified FDD technique to provide massive MIMO gains. The main idea of JSDM is related to grouping users with approximately similar channel covariance. Many machine learning algorithms have been applied to conduct user grouping. In this paper, to improve the user grouping, we employ Reinforcement Guided Competitive Learning (RGCL) to the user grouping and then compare it with clustering techniques, including K-means, and sequential K-means to achieve the appropriate user grouping. The experimental results show that the RGCL technique represents better performance in computational time and system throughput than the other two above mentioned techniques, since RGCL can avoid being trapping in local minima.

scholarly journals Optimal precoder designs for sum rate maximization in MIMO multiuser multicells

2015 ◽  
Vol 18 (3) ◽  
pp. 92-101
Author(s):  
Kha Hoang Ha ◽  
Long Dinh Nguyen ◽  
Tuan Hong Do
Keyword(s):  
Design Problem ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Base Stations ◽  
Transmission Strategy ◽  
Difference Of Convex Functions ◽  
Input Multiple Output ◽  
Difference Of Convex ◽  
Sum Rate ◽  
User Interference

This paper is concerned with the joint linear precoder design problem for the multiuser multiple-input multiple-output (MIMO) heterogeneous networks (HetNets) in which multiple femto base stations (FBSs) coexist with a macro base station (MBS). To tackle the inter-user interference in the macrocell, we exploit the blockdiagonalization scheme and then use the convex optimization to maximize the sum rate of the macrocell. The FBS transmission strategy is to maximize the sum-rate of femtocells subject to the transmitted power constraints per FBS and restrictions on the cross-tier interference to macro-users (MUs). Such a design problem is typically nonconvex, and, thus, challenging to find the FBS precoders. We reformulate the design problem of the FBS precoders as a d.c. (difference of convex functions) programming, and develop an efficient iterative algorithm to obtain the optimal precoders. Numerical simulation results show that the proposed algorithm outperforms the other methods in terms of the total sum-rate of the HetNet.

A Review of Massive Multiple Input Multiple Output for 5G Communication: Benefits and Challenges

2020 ◽  
Vol 1 (1) ◽  
pp. 22-26
Author(s):  
Shaik Nilofer ◽  
Keyword(s):  
Wireless Communication ◽  
Channel Capacity ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
System Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Primary Advantage ◽  
Time Division

Massive MIMO (mMIMO) systems become a primary advantage to overcome the problem of bandwidth restrictions. It improves the channel capacity of remote systems.The paper reviews about mMIMO systems. mMIMO consists of several number of antennas at base station (BS) which improves spectrum efficacy. The extra benefit of the mMIMO system is that the components cost is low because of utilization of less power components. The paper also discusses about the channel estimation at the BS and generally time division mode (TDD) is assumed for mMIMO systems. The paper also discusses system model, benefits for 5G wireless communication and its challenges.

scholarly journals Secure Massive MIMO System with Two-Way Relay Cooperative Transmission in 6G Networks

2020 ◽  
Author(s):  
Yumeng Su ◽  
Hongyuan Gao ◽  
Shibo Zhang
Keyword(s):  
Massive Mimo ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Cooperative Transmission ◽  
Transmission Mode ◽  
Security Issue ◽  
Legitimate User ◽  
Input Multiple Output ◽  
Multiple Relay

Abstract With the advent of Internet of Everything (IoE) and the era of big data, massive multiple-input multiple-output (MIMO) is considered an essential technology to meet the growing communication requirements for beyond 5G and the forthcoming 6G networks. This paper considers a secure massive MIMO system, where the legitimate user and the base station (BS) exchange messages via two-way relays with the presence of passive eavesdroppers. To achieve the trade-off between the physical-layer security and communication reliability, we design a cooperative transmission mode based on multiple-relay collaboration, where some relays broadcast the received signals and other relays act as friendly jammers to prevent the interception by eavesdroppers. A quantum chemical reaction optimization (QCRO) algorithm is proposed to find the most suitable scheme for multiple-relay collaboration. Simulation results highlight excellent performance of the proposed transmission mode under QCRO in different communication scenarios, which can be considered a potential solution for the security issue in future wireless networks.

scholarly journals Transmit and Receive Antenna Selection Based Resource Allocation for Self-Backhaul 5G Massive MIMO HetNets

2021 ◽  
Author(s):  
Farah Akif ◽  
Aqdas Malik ◽  
Ijaz Qureshi ◽  
Ayesha Abassi
Keyword(s):  
Network Performance ◽  
Service Providers ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Base Stations ◽  
Small Cells ◽  
User Association ◽  
Transmit Antenna Selection ◽  
Coverage Area

With the advancement in wireless communication technology, the ease of accessibility and increasing coverage area is a major challenge for service providers. Network densification through Small cell Base Stations (SBS) integration in Heterogeneous Networks (HetNets) promises to improve network performance for cell edge users. Since providing wired backhaul for small cells is not cost effective or practical, the third-Generation Partnership Project (3GPP) has developed architecture for self-backhaul known as Integrated Access and Backhaul (IAB) for Fifth Generation (5G). This allows for Main Base Station (MBS) resources to be shared between SBS and MBS users. However, fair and efficient division of MBS resources remains a problem to be addressed. We develop a novel transmit antenna selection/partitioning technique for taking advantage of IAB 5G standard for Massive Multiple Input Multiple Output (MIMO) HetNets. Transmit antenna resources are divided among access for MBS users and for providing wireless backhaul for SBS. We develop A Genetic Algorithm (GA) based Transmit Antenna Selection (TAS) scheme and compare with random selection, eigenvalue-based selection and bandwidth portioning. Our analysis show that GA based TAS has the ability to converge to an optimum antenna subset providing better rate coverage. Furthermore, we also signify the performance of TAS based partitioning over bandwidth partitioning and also show user association can also be controlled using number of antennas reserved for access or backhaul.

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