Outage Analysis of Cognitive Multihop Networks under Interference Constraints

Abstract-Predicting the digital communication system performance plays a very important role in the process of system design. This performance is usually quantified by symbol error probability or bit error probability. Computing these probabilities in presence of Additive White Gaussian Noise requires to work with integrals involving the Gaussian Qfunction, which cannot be expressed in closed-form in terms of elementary functions. As a result, approximating the Gaussian Q-function in closed-form expressions with high accuracy becomes a necessity. In this paper, we give an overview about the Gaussian Q-function approximations and via some illustrating examples, we discuss their accuracy, tractability as well as their computational complexity.

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“…Let us denote h and f as the channel coefficients of the channels from s → d and from s → p, respectively, we have [39] …”

Section: Average Bep Of Cognitive Underlay Networkmentioning

confidence: 99%

A Survey on Approximations of One-Dimensional Gaussian Q-Function

Bao

Tuyen

Tue

2016

REV-JEC

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“…In this paper, different unlicensed users allocated with different maximum interference power levels is investigated and hence, more general than all previous works with the assumption of the same maximum interference power level for all unlicensed users such as [3,5,6,[8][9][10][11][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. As analysed thoroughly in [3,5,6,11,14,15,18,[24][25][26]29], I m stands implicitly for the interference limit from unlicensed users and excludes interference generated by licensed users. Equivalently, the licensed networks are implicitly assumed to operate reliably for interference levels caused by unlicensed users up to I m , regardless of the interference already existing in these networks.…”

Section: System Modelmentioning

confidence: 99%

“…Several works study the outage probability of underlay DF 1 multi-hop cognitive networks in [3,[5][6][7][8][9][10][11]. More specifically, the outage probability expression for twohop communications was derived in [3,[5][6][7][8][9][10] while the approximate outage probability expression for multihop cognitive networks was proposed in [11].…”

Section: Introductionmentioning

confidence: 99%

“…More specifically, the outage probability expression for twohop communications was derived in [3,[5][6][7][8][9][10] while the approximate outage probability expression for multihop cognitive networks was proposed in [11]. Additionally, the Rayleigh fading was assumed in the analyses in [3,[6][7][8][9]11] while the more flexible Nakagami-m fading model [12] was considered in [5,10]. In the same context, the authors in [13][14][15][16][17][18][19][20][21][22][23][24][25] analyze the outage probability of underlay DF cooperative cognitive networks.…”

Section: Introductionmentioning

confidence: 99%

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On The Performance of Underlay Relay Cognitive Networks

Ho-Van

Bao

2013

REV-JEC

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Abstract-The bit error rate (BER) performance of underlay relay cognitive networks in the presence of Rayleigh fading is thoroughly analyzed in this paper. New exact and asymptotic analytic expressions under consideration of both interference power constraint and maximum transmit power constraint are derived in closed-form and are extensively corroborated by Monte-Carlo simulations. These expressions facilitate in evaluating effectively the network performance behaviour in key operation parameters as well as in optimizing system parameters. A multitude of analytical results expose that underlay relay cognitive networks experience the performance saturation phenomena while their performance considerably depends on the number of hops for the linear network model. Additionally, optimum relay position is significantly dependent of maximum transmit power, maximum interference power, and licensee location. Moreover, the appropriate order of locating unlicensees with different maximum transmit power levels can dramatically improve the network performance.

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“…Specifically, the performance of cognitive dual-hop decode-and-forward (DF) and amplify-andforward (AF) relaying under spectrum-sharing condition have been investigated in [2] and [3], respectively. Extensions to multihop networks have been considered for Rayleigh and Nakagami-m fading channels in [4] and [5], respectively. It has been shown in [4] and [5] that cognitive multihop networks outperform the cognitive single-hop communication and can be considered as an efficient transmission for future wireless systems.…”

Section: Introductionmentioning

confidence: 99%

Cognitive multihop networks in spectrum sharing environment with multiple licensed users

Kim

Duong

Tsiftsis

et al. 2013

2013 IEEE International Conference on Communications (ICC)

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Multihop network has been considered as a breakthrough frontier to enhance the coverage of wireless network. Spectrum-sharing is an efficient technique to enhance the utilization of the limited radio frequency bandwidth. In this paper, we therefore consider the extension of multihop network to cognitive radio networks with the spectrum sharing approach. In particular, we investigate the cognitive multihop networks in the presence of multiple licensed transmitters and receivers. Under the stringent power constraint imposed by the licensed users, we derive the closed-form and asymptotic expressions for the outage probability over Nakagami-m fading channels. The tractable closed-form expressions reveal the impact of important network parameters such as the fading severity parameters of the unlicensed network, the number of licensed users, the peak interference power imposed by the licensed receivers, the interference power from licensed transmitters. A significant observation corroborated by our study shows that the cognitive multihop networks benefit both cognitive radio and multihop networks for improving the coverage extension and frequency spectrum utilization.Index Terms-Multihop network cognitive relay network, Nakagami-m fading, outage probability, outage probability, peak interference power, coverage extension.

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Outage Analysis of Cognitive Multihop Networks under Interference Constraints

Cited by 28 publications

References 11 publications

A Survey on Approximations of One-Dimensional Gaussian Q-Function

A Survey on Approximations of One-Dimensional Gaussian Q-Function

On The Performance of Underlay Relay Cognitive Networks

Cognitive multihop networks in spectrum sharing environment with multiple licensed users

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