The Number of Disconnect MSs and System Capacity Analysis with Variable RSs Location in Two-Hop Cellular Networks

2011 ◽  
Author(s):  
Haokai Chen ◽  
Jian Liang ◽  
Hui Yin ◽  
Zhongnian Li ◽  
Shouyin Liu
Keyword(s):  
Cellular Networks ◽  
System Capacity ◽  
Capacity Analysis

scholarly journals System Capacity Analysis for Ultra-Dense Multi-Tier Future Cellular Networks

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 50503-50512 ◽  
Author(s):  
Syed Waqas Haider Shah ◽  
Adnan Noor Mian ◽  
Shahid Mumtaz ◽  
Jon Crowcroft
Keyword(s):  
Cellular Networks ◽  
System Capacity ◽  
Capacity Analysis

scholarly journals D2D Assisted Cellular Networks in Licensed and Unlicensed Spectrum: Matching-Iteration-Based Joint User Access and Resource Allocation

Algorithms ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 80
Author(s):  
Qiuqi Han ◽  
Guangyuan Zheng ◽  
Chen Xu
Keyword(s):  
Resource Allocation ◽  
Cellular Networks ◽  
System Capacity ◽  
System Throughput ◽  
Unlicensed Spectrum ◽  
Resource Allocation Algorithm ◽  
User Access ◽  
Limited Spectrum

Device-to-Device (D2D) communications, which enable direct communication between nearby user devices over the licensed spectrum, have been considered a key technique to improve spectral efficiency and system throughput in cellular networks (CNs). However, the limited spectrum resources cannot be sufficient to support more cellular users (CUs) and D2D users to meet the growth of the traffic data in future wireless networks. Therefore, Long-Term Evolution-Unlicensed (LTE-U) and D2D-Unlicensed (D2D-U) technologies have been proposed to further enhance system capacity by extending the CUs and D2D users on the unlicensed spectrum for communications. In this paper, we consider an LTE network where the CUs and D2D users are allowed to share the unlicensed spectrum with Wi-Fi users. To maximize the sum rate of all users while guaranteeing each user’s quality of service (QoS), we jointly consider user access and resource allocation. To tackle the formulated problem, we propose a matching-iteration-based joint user access and resource allocation algorithm. Simulation results show that the proposed algorithm can significantly improve system throughput compared to the other benchmark algorithms.

scholarly journals Capacity Analysis of Distributed Antenna Systems with Beamforming

2018 ◽  
Vol 232 ◽  
pp. 04039
Author(s):  
Meiyan Ju ◽  
Chao Chen ◽  
Yueheng Li ◽  
Guoping Tan
Keyword(s):  
Rayleigh Fading ◽  
Path Loss ◽  
Mathematical Expression ◽  
System Capacity ◽  
Capacity Analysis ◽  
Multiple Antenna ◽  
Distributed Antenna Systems ◽  
Multiple Antenna Systems ◽  
Distributed Antenna ◽  
Antenna Systems

Distributed antenna systems (DASs) can reduce the access distance, increase system capacity and improve system performance compared with conventional centralized multiple antenna systems. In this paper, the system capacity of downlink DAS with beamforming is investigated. The mathematical expression of system capacity is derived over the composite channel including Rayleigh fading, shadowing and path loss. At the same time, the interference from other APs is also considered for the studied AP. Numerical methods including Gauss-Hermite integral and composite Simpson’s rule are used to compute the system capacity of DAS under different MS distributions. Numerical results verify the precision of the mathematical analysis of system capacity by comparing Monte-Carlo simulation results. The results also show interference among APs shouldn’t be ignored when APs are close to each other or there are many APs.

scholarly journals Capacity Analysis of IRS-Based UAV Communications with Imperfect Phase Compensation

2021 ◽  
Author(s):  
MOHAMMAD AHMAD Al-Jarrah ◽  
Emad Alsusa ◽  
Arafat Al-Dweik ◽  
Daniel K. C. So
Keyword(s):  
Signal To Noise Ratio ◽  
Phase Error ◽  
Random Variable ◽  
System Capacity ◽  
High Signal ◽  
Capacity Analysis ◽  
Capacity Loss ◽  
Von Mises ◽  
Reflecting Surfaces ◽  
Incident Waves

<div>This paper presents the capacity analysis of unmanned aerial vehicles (UAVs) communications supported by flying intelligent reflecting surfaces (IRSs). In the considered system, some of the UAVs are equipped with an IRS panel that applies certain phase-shifts to the incident waves before being reflected to the receiving UAV. In contrast to existing work, this letter considers the effect of imperfect phase knowledge on the system capacity, where the phase error is modeled as a von Mises random variable with parameter k. Analytical results, corroborated by Monte Carlo simulations, show that the achievable capacity is dependent on the phase error, however, the capacity loss becomes negligible at high signal-to-noise ratio (SNR) and when k>6.</div>

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