Analysis of outage probability for in‐band device‐to‐device communications underlaying cellular network

Ghavami, Hossein; Moghaddam, Shahriar Shirvani

doi:10.1002/dac.3286

Cited by 10 publications

(9 citation statements)

References 20 publications

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“…White noise power spectral density is N 0 /2 = − 174 dBm/Hzfor a signal bandwidth of 180 kHz. Variance of Rayleigh fading ( δ 2 ) is 0.5 …”

Section: Numerical Analyses and Simulation Resultsmentioning

confidence: 99%

“…where δ 2 is the variance of the Rayleigh fading. Using Reference , considering Equations (), the outage probability is given as ().

\begin{matrix} lefttrue \\ P_{{out}_{AF}} & = \sqrt{\frac{2 δ^{2} P_{ij}}{2 δ^{2} P_{ij} - σ^{2}}} \times \underset{1}{\underset{⏟}{true(\int_{0}^{\infty} f_{Y} ((), y) italicdy}} - \int_{0}^{\infty} f_{Y} (y) . \frac{P_{i} (y - γ_{italicth})}{P_{italicij} γ_{italicth} (y + 1) + P_{i} (y - γ_{italicth})} dy) \\ = \sqrt{\frac{2 δ^{2} P_{ij}}{2 δ^{2} P_{ij} - σ^{2}}} - 2 δ^{2} P_{italicij}^{'} P_{i}^{'} P_{i} \sqrt{\frac{P_{ij} P_{ij}^{'}}{((), 2 δ^{2} P_{ij} - σ^{2}) ((), 2 δ^{2} P_{ij}^{'} - σ^{2})}} \times \underset{I}{\underset{⏟}{\int_{0}^{\infty} {(\frac{1}{P_{i}^{'} + {yP}_{ij}^{'}})}^{2} \times \frac{(y - γ_{italicth})}{P_{ij} γ_{th} ((), y + 1) + P_{i} ((), y - γ_{th})} italicdy}} . \end{matrix}

…”

Section: Outage Probability For No‐ib Relay‐aided D2d Communicationsmentioning

confidence: 99%

“…As shown in Reference , CDFs of X and Y are respectively as Equations () and (). Using Equation (), the outage probability for the DF protocol is as Equation ().…”

Section: Outage Probability For No‐ib Relay‐aided D2d Communicationsmentioning

confidence: 99%

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Outage analysis of nonorthogonal in‐band relay‐aided device‐to‐device communications in Rayleigh fading channels

Moghaddam

2017

Internet Technology Letters

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Minimizing the outage probability and/or maximizing the throughput, optimally realize relay‐aided nonorthogonal in‐band (NO‐IB) device‐to‐device (D2D) communications. In this letter, we derive closed‐form expressions for the outage probability of NO‐IB amplify‐and‐forward (AF) and decode‐and‐forward (DF) relay‐aided D2D communications in Rayleigh fading channels. Numerical analyses show that the closed‐form formulas are in close agreement with the simulation results. Furthermore, we investigate the effect of signal‐to‐noise ratio and the distances between D2D pairs and relay nodes as well as cellular users. First results show that in the low‐noise regime, AF outperforms DF while they perform very close in the moderate noise level and DF outperforms AF in the high‐noise power. Second, we indicate that the relay‐aided AF/DF D2D communications is more reliable than the direct one when the TX/RX nodes of a D2D pair is distant approximately more than half of the cell radius.

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“…White noise power spectral density is N 0 /2 = − 174 dBm/Hzfor a signal bandwidth of 180 kHz. Variance of Rayleigh fading ( δ 2 ) is 0.5 …”

Section: Numerical Analyses and Simulation Resultsmentioning

confidence: 99%

“…where δ 2 is the variance of the Rayleigh fading. Using Reference , considering Equations (), the outage probability is given as ().

\begin{matrix} lefttrue \\ P_{{out}_{AF}} & = \sqrt{\frac{2 δ^{2} P_{ij}}{2 δ^{2} P_{ij} - σ^{2}}} \times \underset{1}{\underset{⏟}{true(\int_{0}^{\infty} f_{Y} ((), y) italicdy}} - \int_{0}^{\infty} f_{Y} (y) . \frac{P_{i} (y - γ_{italicth})}{P_{italicij} γ_{italicth} (y + 1) + P_{i} (y - γ_{italicth})} dy) \\ = \sqrt{\frac{2 δ^{2} P_{ij}}{2 δ^{2} P_{ij} - σ^{2}}} - 2 δ^{2} P_{italicij}^{'} P_{i}^{'} P_{i} \sqrt{\frac{P_{ij} P_{ij}^{'}}{((), 2 δ^{2} P_{ij} - σ^{2}) ((), 2 δ^{2} P_{ij}^{'} - σ^{2})}} \times \underset{I}{\underset{⏟}{\int_{0}^{\infty} {(\frac{1}{P_{i}^{'} + {yP}_{ij}^{'}})}^{2} \times \frac{(y - γ_{italicth})}{P_{ij} γ_{th} ((), y + 1) + P_{i} ((), y - γ_{th})} italicdy}} . \end{matrix}

…”

Section: Outage Probability For No‐ib Relay‐aided D2d Communicationsmentioning

confidence: 99%

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Outage analysis of nonorthogonal in‐band relay‐aided device‐to‐device communications in Rayleigh fading channels

Moghaddam

2017

Internet Technology Letters

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“…D2D pairs, directly or through a relay, overlay, or underlay or in-band or out-band, transmit and receive the signal [34,35]. By using D2D communications, the delay and the traffic load of the main network decrease, the spectral efficiency increases, and the consumed energy and cost reduce [36]. In order to do the optimum resource allocation in D2D communications, we have two approaches.…”

Section: D2d Communicationsmentioning

confidence: 99%

Introductory Chapter: Primary and Secondary Users in Cognitive Radio-Based Wireless Communication Systems

Moghaddam¹

2018

Cognitive Radio in 4g/5g Wireless Communication Systems

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Additional information is available at the end of the chapter 1. Wireless communications and the necessity of cognitive radio Wireless communication systems play a special role in human life, facilitate the life, and change the world much more in the future. The diversity of applications and services of wireless communications indicates the widespread use of wireless systems and equipment in the future. Since the first radio link by Marconi in 1896, it has been more than 120 years, and several wireless communication systems have been introduced up to now. Meanwhile, the advancement of cellular wireless communications, whose idea came back to 1947 and their first generation in 1978 (namely advanced mobile phone service), has been well adopted and has grown dramatically, so that the researchers and operators are focused on standardization and design of 5G and 6G wireless communication systems [1]. From the beginning, one of the main problems in wireless communications is the scarcity of radio resources (frequency, time, and power). In recent years, the lack of frequency spectrum and the necessity of frequency reuse at different times and places and reduction of the consumed power are of great importance. Looking at the following laws: • Moore's law: The number of transistors that can be cheaply placed on a microchip doubles and the computer power exponentially increases approximately every 2 years [2] • Cooper's law: The number of voice calls or data that can be sent over the usable radio spectrum doubles every 30 months [2]

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“…Device to device (D2D) communications in 3GPP and LTE standards offers transfer of data directly to each other without the involvement of BSs [6]. Operation Megacommunications concept), with guaranteed QoS requirements of wireless services [7].…”

Section: Advancement Of Wireless Technologies From 1g To 5gmentioning

confidence: 99%

Spectrum Decision Framework to Support Cognitive Radio Based IoT in 5G

Akhtar¹,

Arif²,

Siddique³

2018

Cognitive Radio in 4g/5g Wireless Communication Systems

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RF Spectrum Decision in Cognitive Radio enables unlicensed users of wireless communication systems to occupy the vacant spectrum slots as a solution to scarce spectrum. Internet of Things (IoT) is a wide-reaching network of unified entities. IoT capable things will be interconnected through wireless communication technologies offering cost-effectiveness and accessibility to remote users making quality life style. IoT implementation suffers from challenges of vulnerabilities to dynamic environmental conditions, ease of access, bandwidth allocation and utilization, and cost to purchase RF spectrum. As RF spectrum is a precious commodity and there is a dearth of RF spectrum, hence IoT connections are drifting towards Cognitive Radio Networks (CRNs). Permeating things with cognitive abilities will be able to make RF spectrum decisions to achieve interference-free and wireless connectivity as per their QoS requirements. The wireless systems are rapidly advancing. The leap from packet switching along with circuit switching with 144 kbps data rate (2G and 2.5G) to Long Term Evolution Advanced (LTE-A), i.e., 4G occurred in one decade time frame. As the current wireless connectivity is aimed at higher capacity, higher data rate, low end-to-end latency, massive device connectivity, reduced cost and consistent Quality of Experience (QoE) provision, therefore, 4G is being replaced with 5G. Presently the Radio Frequency (RF) spectrum band is fully sold out and allocated to various wireless operators and applications. On the other hand, new wireless applications are emerging and there is a serious dearth of frequency spectrum to be allocated to emerging wireless services. The efficient utilization of assigned RF spectrum which is otherwise underutilized due to the typical usage by the licensed users known as Primary Users (PUs) is the one of the best possible way to implement IoT in 5G. Thus the Spectrum Decision by unlicensed users of CR holds a significance in CR-based IoT in 5G and beyond network. This chapter describes a scientific supported spectrum decision support framework for CR Network. The main goal of this chapter is to discuss how CR technology can be helpful for the IoT paradigm.

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Analysis of outage probability for in‐band device‐to‐device communications underlaying cellular network

Cited by 10 publications

References 20 publications

Outage analysis of nonorthogonal in‐band relay‐aided device‐to‐device communications in Rayleigh fading channels

Outage analysis of nonorthogonal in‐band relay‐aided device‐to‐device communications in Rayleigh fading channels

Introductory Chapter: Primary and Secondary Users in Cognitive Radio-Based Wireless Communication Systems

Spectrum Decision Framework to Support Cognitive Radio Based IoT in 5G

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