scholarly journals Virtual MIMO Beamforming and Device Pairing Enabled by Device-to-Device Communications for Multidevice Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Yeonjin Jeong ◽  
Jooheum Yoon ◽  
Sang Hyun Lee ◽  
Yun Hee Kim
Keyword(s):  
Multiple Input Multiple Output ◽  
Access Point ◽  
D2d Communications ◽  
Channel State ◽  
Multiple Input ◽  
Device To Device ◽  
Input Multiple Output ◽  
Sum Rate ◽  
Device Pairing ◽  
The Internet Of Things

We consider a multidevice network with asymmetric antenna configurations which supports not only communications between an access point and devices but also device-to-device (D2D) communications for the Internet of things. For the network, we propose the transmit and receive beamforming with the channel state information (CSI) for virtual multiple-input multiple-output (MIMO) enabled by D2D receive cooperation. We analyze the sum rate achieved by a device pair in the proposed method and identify the strategies to improve the sum rate of the device pair. We next present a distributed algorithm and its equivalent algorithm for device pairing to maximize the throughput of the multidevice network. Simulation results confirm the advantages of the transmit CSI and D2D cooperation as well as the validity of the distributive algorithm.

The Security Risks and Challenges of 5G Communications

2021 ◽  
Vol 3 (2) ◽  
pp. 46-53
Author(s):  
Young B. Choi ◽  
Matthew E. Bunn
Keyword(s):  
Multiple Input Multiple Output ◽  
Wireless Systems ◽  
Daily Basis ◽  
Automated Manufacturing ◽  
Security Risks ◽  
Security Challenges ◽  
Autonomous Cars ◽  
Multiple Input ◽  
Input Multiple Output ◽  
The Internet Of Things

With the introduction of the 5th generation of wireless systems and communications (5G) comes new risks and challenges. This paper explores the potential security challenges of 5G communication compared with legacy cellular networks and prior generations of communication standards. This paper defines what 5G is and how it affects our lives on a daily basis. It further discusses the new security features involving different technologies applied to 5G, such as heterogeneous networks, device-to-device communications, massive multiple-input multiple-output, software-defined networks, and the internet of things, including autonomous cars, healthcare, automated manufacturing, and more.

scholarly journals Energy and Information Beamforming in Airborne Massive MIMO System for Wireless Powered Communications

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3540 ◽  
Author(s):  
Yurong Wang ◽  
Aijun Liu ◽  
Kui Xu ◽  
Xiaochen Xia
Keyword(s):  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Hardware Complexity ◽  
Mimo Channels ◽  
Channel State ◽  
Active Antennas ◽  
Large Numbers ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Critical Problems

Energy supply and information backhaul are critical problems for wireless sensor networks deployed in remote places with poor infrastructure. To deal with these problems, this paper proposes an airborne massive multiple-input multiple-output (MIMO) system for wireless energy transfer (WET) and information transmission. An air platform (AP) equipped with a two-dimensional rectangular antenna array is employed to broadcast energy and provide wireless access for ground sensors. By exploiting the statistical property of air-terrestrial MIMO channels, the energy and information beamformers are jointly designed to maximize the average received signal-to-interference-plus-noise ratio (SINR), which gives rise to a statistical max-SINR beamforming scheme. The scheme does not rely on the instantaneous channel state information, but still requires large numbers of RF chains at AP. To deal with this problem, a heuristic strongest-path energy and information beamforming scheme is proposed, which can be implemented in the analog-domain with low computational and hardware complexity. The analysis of the relation between the two schemes reveals that, with proper sensor scheduling, the strongest-path beamforming is equivalent to the statistical max-SINR beamforming when the number of AP antennas tends to infinity. Using the asymptotic approximation of average received SINR at AP, the system parameters, including transmit power, number of active antennas of AP and duration of WET phase, are optimized jointly to maximize the system energy efficiency. The simulation results demonstrate that the proposed schemes achieve a good tradeoff between system performance and complexity.

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 Mitigating the Interference Caused by Pilot Contamination in Multi-cell Massive Multiple Input Multiple Output Systems Using Low Density Parity Check Codes in Uplink Scenario

2020 ◽  
Vol 37 (6) ◽  
pp. 1061-1074
Author(s):  
Lokesh Bhardwaj ◽  
Ritesh Kumar Mishra
Keyword(s):  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Low Density ◽  
Pilot Contamination ◽  
Parity Check ◽  
Low Density Parity Check ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Sum Rate

The effects of pilot contamination (PC) on the performance of multi-cell multi-user massive multiple input multiple output (MC-MU-m-MIMO) system in uplink has been analyzed in this article. In a multi-cell scenario, the channel estimation (CE) at the desired cell using pilot reuse to avoid significant overhead results in poor CE due to PC. The improvement in degraded performance due to the effect of PC has been shown using low Density Parity Check (LDPC) codes. The comparative analysis of performance in terms of variation in bit error rate (BER) with the signal to noise ratio (SNR) for LDPC coded and uncoded information blocks of users has been shown when the number of cells sharing the same frequency band is varied. Further, the expression for sum-rate has been derived and its variation with the number of base station (BS) antennas has also been shown. The simulated results have shown that the LDPC coded scheme performs better than the uncoded counterpart and the sum-rate capacity increases when the strength of channel coefficients between the BS antennas of the desired cell and the users of remaining cells is less.

scholarly journals Pilot Decontamination Using Asynchronous Fractional Pilot Scheduling in Massive MIMO Systems

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6213
Author(s):  
Muhammad Irshad Zahoor ◽  
Zheng Dou ◽  
Syed Bilal Hussain Shah ◽  
Imran Ullah Khan ◽  
Sikander Ayub ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Ideal Number ◽  
Sum Rate ◽  
Inter Cell Interference ◽  
Time Division

Due to large spectral efficiency and low power consumption, the Massive Multiple-Input-Multiple-Output (MIMO) became a promising technology for the 5G system. However, pilot contamination (PC) limits the performance of massive MIMO systems. Therefore, two pilot scheduling schemes (i.e., Fractional Pilot Reuse (FPR) and asynchronous fractional pilot scheduling scheme (AFPS)) are proposed, which significantly mitigated the PC in the uplink time division duplex (TDD) massive MIMO system. In the FPR scheme, all the users are distributed into the central cell and edge cell users depending upon their signal to interference plus noise ratio (SINR). Further, the capacity of central and edge users is derived in terms of sum-rate, and the ideal number of the pilot is calculated which significantly maximized the sum rate. In the proposed AFPS scheme, the users are grouped into central users and edge users depending upon the interference they receive. The central users are assigned the same set of pilots because these users are less affected by interference, while the edge users are assigned the orthogonal pilots because these users are severely affected by interference. Consequently, the pilot overhead is reduced and inter-cell interference (ICI) is minimized. Further, results verify that the proposed schemes outperform the previous proposed traditional schemes, in terms of improved sum rates.

scholarly journals Implementation of Deep Learning in Spatial Multiplexing MIMO Communication

2018 ◽  
Vol 12 (2) ◽  
pp. 699
Author(s):  
Mahdin Rohmatillah ◽  
Hadi Suyono ◽  
Rahmadwati Rahmadwati ◽  
Sholeh Hadi Pramono
Keyword(s):  
Communication System ◽  
Additive White Gaussian Noise ◽  
Multiple Input Multiple Output ◽  
Spatial Multiplexing ◽  
Channel State ◽  
Mimo Communication ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Parametric Rectified Linear Unit ◽  
Channel Impairment

Research in Multiple Input Multiple Output (MIMO) communication system has been developed rapidly in order to improve the effectiveness of communication among users. However, trade-off phenomenon between performance and computational complexity always become the hugest dilemma suffered by researchers. As an alternative solution, this paper proposes an optimization in 3x3 spatial multiplexing MIMO communication system using end-to-end based learning, specifically, it adapts autoencoder based model with the knowledge of Channel State Information (CSI) in the receiver side, make it fairly compared with the baseline method. The proposed models were evaluated in one of the most common channel impairment which is fast Rayleigh fading with additional Additive White Gaussian Noise (AWGN). By appropriately determining hyperparameters and the help of PReLU (Parametric Rectified Linear Unit), the results show that this autoencoder based MIMO communication system results in very promising results by exceeding the baseline methods (methods widely used in conventional MIMO communication) by reaching BER lower than at SNR 22.5 dB.

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