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.

scholarly journals Performance analysis of IEEE 802.11ac based WLAN in wireless communication systems

2019 ◽  
Vol 9 (2) ◽  
pp. 1131 ◽  
Author(s):  
A. Z. Yonis
Keyword(s):  
Communication Systems ◽  
Wireless Local Area Network ◽  
Local Area Network ◽  
Multiple Input Multiple Output ◽  
Local Area ◽  
Area Network ◽  
Data Rates ◽  
Input Multiple Output ◽  
Ieee 802.11Ac ◽  
5 Ghz

<p><span lang="EN-US">IEEE 802.11ac based wireless local area network (WLAN) is emerging WiFi standard at 5 GHz, it is new gigabit-per-second standard providing premium services. IEEE 802.11ac accomplishes its crude speed increment by pushing on three distinct measurements firstly is more channel holding, expanded from a maximum of 80 MHz up to 160 MHz modes. Secondly, the denser modulation, now using 256-QAM, it has the ability to increase the data rates up to 7 Gbps using an 8×8 multiple input multiple output (MIMO). Finally, it provides high resolution for both narrow and medium bandwidth channels. This work presents a study to improve the performance of IEEE 802.11ac based WLAN system.</span></p>

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 Total Local Dose in Hypothetical 5G Mobile Networks for Varied Topologies and User Scenarios

2020 ◽  
Vol 10 (17) ◽  
pp. 5971 ◽  
Author(s):  
Sven Kuehn ◽  
Serge Pfeifer ◽  
Niels Kuster
Keyword(s):  
Mobile Networks ◽  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Monte Carlo Analysis ◽  
5G Networks ◽  
Fifth Generation ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Network Topologies ◽  
5G Mobile Networks

In this study, the total electromagnetic dose, i.e., the combined dose from fixed antennas and mobile devices, was estimated for a number of hypothetical network topologies for implementation in Switzerland to support the deployment of fifth generation (5G) mobile communication systems while maintaining exposure guidelines for public safety. In this study, we consider frequency range 1 (FR1) and various user scenarios. The estimated dose in hypothetical 5G networks was extrapolated from measurements in one of the Swiss 4G networks and by means of Monte Carlo analysis. The results show that the peak dose is always dominated by an individual’s mobile phone and, in the case of non-users, by the bystanders’ mobile phones. The reduction in cell size and the separation of indoor and outdoor coverage can substantially reduce the total dose by >10 dB. The introduction of higher frequencies in 5G mobile networks, e.g., 3.6 GHz, reduces the specific absorption rate (SAR) in the entire brain by an average of −8 dB, while the SAR in the superficial tissues of the brain remains locally constant, i.e., within ±3 dB. Data from real networks with multiple-input multiple-output (MIMO) were not available; the effect of adaptive beam-forming antennas on the dose will need to be quantitatively revisited when 5G networks are fully established.

scholarly journals Artificial Intelligence Based LTE MIMO Antenna for 5th Generation Mobile Networks

2020 ◽  
Vol 2 (3) ◽  
pp. 155-162
Author(s):  
Dr. Abul Bashar
Keyword(s):  
Artificial Intelligence ◽  
Mobile Networks ◽  
Multiple Input Multiple Output ◽  
Long Term Evolution ◽  
Base Station ◽  
Fifth Generation ◽  
Term Evolution ◽  
Multiple Input ◽  
Input Multiple Output

Artificial intelligence based long term evolution multi in multi output antenna supporting the fifth generation mobile networks is put forth in the paper. The mechanism laid out in paper is devised using the monopole-antenna integrated with the switchable pattern. The long term evolution based multiple input and multiple output antenna is equipped with four antennas and capable of providing a four concurrent data streams quadrupling the theoretical maximum speed of data transfer allowing the base station to convey four diverse signals through four diverse transmit antennas for a single user equipment. The utilization of the long term evolution multiple input multiple output is capable of utilizing the multi-trial broadcasting to offer betterments in the signal performance as well as throughput and spectral efficiency when used along the fifth generation mobile networks. So the paper proposes the artificial intelligence based long term evolution multiple input multiple output four transmit antenna with four diverse signal transmission capacity that is operating in the frequency of 3.501 Gigahertz frequency. The laid out design is evaluated using the Multi-input Multi output signal analyzer to acquire the capacity of the passive conveyance of the various antennas with the diverse combination of patterns. The outcomes observed enables the artificial intelligence antenna to identify the choicest antenna to be integrated in the diverse environments for improving the throughput, signal performance and the data conveyance speed.

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 Multiple Power Allocation Game Schemes for Spectrum Coexistence Model Between Multistatic MIMO Radar Sensors and MU Communication

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6216
Author(s):  
Bin He ◽  
Hongtao Su
Keyword(s):  
Power Allocation ◽  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Iterative Algorithms ◽  
Mimo Radar ◽  
Base Station ◽  
Radar Sensors ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Study Power

The normal operations of radar systems and communication systems under the condition of spectrum coexistence are facing a huge challenge. This paper uses game theory to study power allocation problems between multistatic multiple-input multiple-output (MIMO) radars and downlink communication. In the case of spectrum coexistence, radars, base station (BS) and multi-user (MU) have the working state of receiving and transmitting signals, which can cause unnecessary interferences to different systems. Therefore, when they work together, they should try to suppress mutual interferences. Firstly, the signal from BS is considered as interference when radar detects and tracks targets. A supermodular power allocation game (PAG) model is established and the existence and uniqueness of the Nash equilibrium (NE) in this game are proved. In addition, the power allocation problem from BS to MU is also analyzed, and two Stackelberg PAG models are constructed. It is proved that the NE of each game exists and is unique. Simultaneously, two Stackelberg power allocation iterative algorithms converge to the NEs. Finally, numerical results verify the convergence of the proposed PAG algorithms.

scholarly journals A Low Complexity Near-Optimal Iterative Linear Detector for Massive MIMO in Realistic Radio Channels of 5G Communication Systems

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 388 ◽  
Author(s):  
Mahmoud A. Albreem ◽  
Mohammed H. Alsharif ◽  
Sunghwan Kim
Keyword(s):  
Communication Systems ◽  
Radio Channel ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Base Station ◽  
Matrix Inversion ◽  
Linear Detector ◽  
Radio Channels ◽  
Inversion Methods ◽  
Input Multiple Output

Massive multiple-input multiple-output (M-MIMO) is a substantial pillar in fifth generation (5G) mobile communication systems. Although the maximum likelihood (ML) detector attains the optimum performance, it has an exponential complexity. Linear detectors are one of the substitutions and they are comparatively simple to implement. Unfortunately, they sustain a considerable performance loss in high loaded systems. They also include a matrix inversion which is not hardware-friendly. In addition, if the channel matrix is singular or nearly singular, the system will be classified as an ill-conditioned and hence, the signal cannot be equalized. To defeat the inherent noise enhancement, iterative matrix inversion methods are used in the detectors’ design where approximate matrix inversion is replacing the exact computation. In this paper, we study a linear detector based on iterative matrix inversion methods in realistic radio channels called QUAsi Deterministic RadIo channel GenerAtor (QuaDRiGa) package. Numerical results illustrate that the conjugate-gradient (CG) method is numerically robust and obtains the best performance with lowest number of multiplications. In the QuaDRiGA environment, iterative methods crave large n to obtain a pleasurable performance. This paper also shows that when the ratio between the user antennas and base station (BS) antennas ( β ) is close to 1, iterative matrix inversion methods are not attaining a good detector’s performance.

scholarly journals Orbital Angular Momentum-Based Multiple-Input-Multiple-Output with Receive Antenna Shift Keying for 6G

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1567
Author(s):  
Sang-Hoon Lee ◽  
Ahmed Al Al Amin ◽  
Soo-Young Shin
Keyword(s):  
Angular Momentum ◽  
Wireless Communication ◽  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Wireless Communication Systems ◽  
Time Code ◽  
Multiple Input ◽  
Shift Keying ◽  
Input Multiple Output ◽  
Receive Antenna

Spectral efficiency is a major concern for future 6G wireless communication systems. Thus, an appropriate scheme is needed to provide channel capacity improvement for multiple transmitters and receiver-based wireless communication systems without consuming extra resource for communication (e.g., frequency/time/code) or causing interference. Therefore, to fulfill the mentioned requirements for the future 6G wireless network, orbital angular momentum-based multiple-input-multiple-output (OAM-MIMO) multiplexing technique is incorporated with the receive antenna shift keying (RASK) technique in this study (termed as the OAM-MIMO-RASK scheme). OAM-MIMO-RASK can transfer multiple symbols from multiple transmitters to different receivers simultaneously by using multiple subchannels using the OAM and RASK techniques without any interference or additional resource (frequency/time/code). The numerical results illustrated that the proposed OAM-MIMO-RASK can achieve almost double capacity than the existing OAM-MIMO scheme and significantly higher capacity than the existing RASK-based scheme for different values of signal-to-noise ratio. Moreover, the simulation result is validated by the theoretical result which is also shown by the numerical result. In addition, due to different normalized distances from the transmitters and receivers, the proposed OAM-MIMO-RASK scheme can achieve almost double capacity than the existing OAM-MIMO scheme by using OAM-MIMO and RASK technique effectively which is also depicted by the numerical results.

scholarly journals 5G Downlink Throughput Enhancement by Beams Consolidating at Vacant Traffic

2019 ◽  
Vol 15 (4) ◽  
Author(s):  
Ali Othman Al Janaby
Keyword(s):  
Mobile Networks ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Throughput Enhancement ◽  
Coding Scheme ◽  
Simulation Evaluation ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Technology ◽  
5G Mobile Networks

The 3GPP release for 5G (R15) assigns each User Equipment (UE) a radio beam by employing Massive Multi-User MU-Multiple-Input-Multiple-Output (MIMO) technology. Each beam carries, at the downlink, a data rate according to the modulation and coding scheme (MCS) assigned by the base station (BS). For the limited existence of active UEs and during vacant traffic or standby UEs, the assigned beams will be transmitted, but not to any UE. This paper proposes a new scheme that consolidates vacant beams of inactive UEs, to the adjacent beam of the active UE or UE at the cell edge to duplicate the bandwidth of the new beam. The proposed scheme increases the level of desired modulation and coding scheme (MCS) to a higher scheme and hence enhances the spectral efficiency (SE) of the 5G mobile networks. Specifically, the BS consolidates (combines) multiple radio beams along with the assigned beam during vacant traffic. More than two beams are consolidated in particular to the active UE to increase the bit rate by assigning higher MCS. The simulation evaluation depicted that the performance of beams consolidation provides a gain of 3.5 dB above than the state before beams consolidation. Moreover, more than 40 % improvement in UE throughput is achieved.

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