Massive Relaying Communication System Under IQ Imbalance and Hardware Manufacturing Problems

El‐Mashed, Mohamed G.

doi:10.1109/jsyst.2019.2891564

Cited by 10 publications

(5 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The channel amplitudes | | can be described as independent and non-identically distributed Nakagami-m fading, with shape parameters and scale parameters The channel gains are *| | + . The channel gains probability density functions (PDFs) and cumulative distribution functions (CDFs), are [24][25]:…”

Section: The Proposed Mult-hop Communication System Under Hardware Ma...mentioning

confidence: 99%

Design of Multihop Communication Systems Under Hardware Manufacturing Defects and Self Interference

et al. 2022

Self Cite

View full text Add to dashboard Cite

Most studies on multi-hop communication systems are actually based on the assumption that hardware parts are built with high quality transmit/receive radio frequency chains, which are expensive and power-hungry. In practice, low cost hardware components are employed, which are prone to hardware manufacturing defects (e.g., phase noise, nonlinear power amplifier, inphase/quadrature imbalance, nonlinear low noise amplifier and analog to digital converter impairments). This paper focuses on the design of the transmitter, relay stations (RSs) and receiver for multi-hop communication systems under hardware defects. This paper analyzes the hardware defects and their impacts o n the performance of multi-hop communication system. In addition, the impact of self-interference at the RSs is considered. The effect of hardware defects is modeled using distortion noises. A closed-form expression for the signal to noise and distortion ratios (SNDRs) is mathematically derived, then the performance metrics (i.e., SNDR, outage probability (OP) and ergodic capacity) are calculated, accounting for hardware defects. In addition, exact form expression of the average bit error probability is derived. To facilitate comparison, performance metrics of the proposed multi-hop relaying system and ideal system are illustrated. We also propose a linear minimum mean square error (LMMSE) and self-interference cancellation technique to mitigate the hardware defects. The results reveal that hardware defects can degrade the system performance. In addition, SNDR ceiling is inversely proportional to the summation of the square of hardware defect lev el. Also, the proposed mitigation technique can enhance the syst em performance.INDEX TERM Multi-hop system, hardware defects, self-interference, outage, ergodic capacity, bit error probability. I. INTRODUCTION A. BackgroundTransmission-based multi-hop is a promising scheme to obtain wider coverage and to overcome wireless channels impairment. The main goal is that communication is verified via relaying the data from the transmitter to the receiver through many intermediate relays in between. Multi-hop communication systems have a number of features over classical communication systems in the fields of capacity, deployment, and connectivity, enhanced coverage, throughput, and power/battery life while decreasing the demand for specific infrastructureRelaying schemes enable network connectivity where classical architectures are difficult to implement because of constraints of the location, and can also be implemented to wireless local area networks, cellular networks , and hybrid networks. In multi-hop systems, the transmitter can communicate with the receiver via a number of relay stations (RSs). Therefore, multi-hop systems have the property of extending the coverage without applying higher transmission power.

show abstract

Section: The Proposed Mult-hop Communication System Under Hardware Ma...mentioning

confidence: 99%

Design of Multihop Communication Systems Under Hardware Manufacturing Defects and Self Interference

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…MmWave transceivers are equipped with many antennas that are grouped into a small area. However, assigning a unique chain of radio frequency (RF) for each antenna is difficult to implement because of high cost, high hardware complexity and the high power consumption [4] - [5]. For different military and civilian applications, it has become important for wireless networks to secure the private data such as credit card transaction, on-line personal information, and intelligent transmissions [6].…”

Section: Introductionmentioning

confidence: 99%

Efficient Security Architecture for Physical Layer in mmWave Communication Systems

et al. 2022

Self Cite

View full text Add to dashboard Cite

Employing mmWave is a good way to achieve the data demands for the new and future generations of communication systems. In order to decrease power consumption and complexity of hardware, hybrid precoding is implemented for mmWave systems with large scale antenna. Lack of secure communication paths in mmWave multiple-input multiple-output (MIMO) systems leads to attack and degrade the system efficiency. For secure communications, this paper proposes a deep and secure hybrid precoder and decoder design for mmWave MIMO systems to maximize the secrecy rate. Lack of secure communication paths being eavesdropped by Eves is illustrated and the scatterer sharing channel model is assumed. The proposed algorithm consists of two convolutional neural networks for calculating the secure RF analog precoder, and then obtains the digital precoder that can further improve the security. In addition, singular value decomposition technique based physical layer security is implemented to determine digital precoders. Results showed that the secrecy performance improvement of the proposed algorithm in comparison to the benchmark algorithms and algorithms based on optimization methods.INDEX TERMS mmWave, physical layer security, Eves, secrecy rate, digital precoder and analog precoder.

show abstract

“…2 On the other hand, massive multiple-input multiple-output (MIMO) systems are widely seen a significant technology for the cellular network. 3,4 Such systems may give lower transmitted power with straight forward signal processing and can increase the energy efficiency (EE) by several orders of magnitude.…”

Section: Introductionmentioning

confidence: 99%

Data and pilot power controls scheme based on convolutional neural network for massive cellular system with underlaid device‐to‐device communications

Faragallah

El‐Sayed

El‐Mashed

2022

Int J Communication

View full text Add to dashboard Cite

Studying deep learning framework in massive cellular system to optimize its performance is a challenge task. In this paper, multi-cell massive cellular system with device-to-device (D2D) communication is studied, where D2D pairs and cellular users can share different orthogonal pilots to overcome interference at the cellular base station (BS). We propose data and pilot power controls scheme based on deep learning framework using convolutional neural network (CNN) for cellular and D2D users. The main focus is to obtain the optimal data and pilot powers (i.e., cellular pilot power, p pilot Cellular User , cellular data power, p Cellular User , D2D pilot power, p pilot D2D , and D2D data power, p D2D ) for maximum spectral efficiency (SE). SE optimization problem is formulated with the goal of obtaining optimal transmit powers. Also, comparison between the proposed scheme and the iterative power control schemes (i.e., weighted minimum mean square error [MMSE] technique, bisection technique, and technique-based geometric mean per-cell max-min fairness) is provided.Results show that the proposed scheme can increase the sum SE of multi-cell massive cellular system with D2D communications.

show abstract

Massive Relaying Communication System Under IQ Imbalance and Hardware Manufacturing Problems

Cited by 10 publications

References 27 publications

Design of Multihop Communication Systems Under Hardware Manufacturing Defects and Self Interference

Design of Multihop Communication Systems Under Hardware Manufacturing Defects and Self Interference

Efficient Security Architecture for Physical Layer in mmWave Communication Systems

Data and pilot power controls scheme based on convolutional neural network for massive cellular system with underlaid device‐to‐device communications

Contact Info

Product

Resources

About