Performance analysis of relay selection schemes in underlay cognitive networks with Decode and Forward relaying

Chamkhia, Hela; Hasna, Mazen O.; Hamila, Ridha; Hussain, Syed Imtiaz

doi:10.1109/pimrc.2012.6362594

Cited by 26 publications

(17 citation statements)

References 12 publications

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“…This metric is conditioned on the maximum transmit power at the relay and the maximum tolerated interference power level at the primary user. In [13], three relay selection scenarios were proposed, the relay with the best second hop, the relay with worst second hop, and the relay satisfying the minimum level of interference with the primary user. Closed-form expressions for the outage and error probabilities were derived assuming Rayleigh fading channels.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of cognitive AF relay networks with multiuser switched diversity in Rayleigh fading channels

Salhab

Zummo

2017

J Wireless Com Network

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The multiuser switched diversity (MUSwiD) selection schemes are useful in reducing the required channel estimation load in wireless networks. In this paper, we propose and evaluate the performance of cognitive amplify-and-forward (AF) MUSwiD relay networks where a cognitive user is selected among a set of users for data reception. The selection process is performed such that the end-to-end (e2e) signal-to-noise ratio (SNR) of the selected user satisfies a predetermined switching threshold. Such a user that satisfies this threshold is scheduled instead of the best user to receive its message from the secondary source. In the proposed system, we consider a cognitive source, a cognitive relay, a set of cognitive users, and a primary user. In this paper, an upper bound on the e2e SNR of a user is used in deriving of closed-form approximations for the outage probability and average symbol error probability (ASEP) of the studied system in addition to deriving the ergodic channel capacity. To get more about system insights, the performance is studied at the high SNR regime where approximate expressions for the outage probability, SEP, diversity order, and coding gain are derived. The derived analytical and asymptotic expressions are verified by Monte-Carlo simulations, and some numerical examples are provided to illustrate the effect of some parameters such as number of users and switching threshold on the system performance. Findings illustrate that the diversity order of the studied cognitive AF multiuser switched diversity relaying network is the same as its non-cognitive counterpart. Also, results show that the asymptotic results tightly converge to the exact ones, and the analytical bounds are indeed very tight, validating the accuracy of our approach of analysis. Furthermore, findings illustrate that the proposed MUSwiD user selection schemes are efficient in the range of low SNR values, which makes them attractive options for practical implementation in emerging mobile broadband communication systems. In contrast, these selection schemes are shown to be inefficient in the range of high SNR values where the multiuser diversity gain is noticeably degraded when they are implemented.

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Section: Introductionmentioning

confidence: 99%

Performance analysis of cognitive AF relay networks with multiuser switched diversity in Rayleigh fading channels

Salhab

Zummo

2017

J Wireless Com Network

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“…1 It should be emphasized that the analysis presented in this paper is completely different and more complicated than [26] for the following reasons: Firstly, the relay selection scheme considered in this paper is different from that in [26]; the former is a capacity-optimal selection scheme while the latter is not. Secondly, we consider both interference power and maximum transmit power constraints whereas, [26] only considers the interference power constraint, which definitely renders the analysis presented hereinafter more complex than [26].…”

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confidence: 99%

“…For instance, in the method of [3,24], the selected relay is the one that maximizes the end-toend signal-to-noise ratio (SNR). The authors in [6][7][8]25] select the relay among all possible candidates (i.e., all relays are assumed to successfully decode source information) that results in the largest SNR at the destination while the authors in [26] opt for the relay among all possible candidates (i.e., relays are assumed to satisfy the interference power constraint) that results in either the largest or smallest SNR at the destination, or the minimum level of interference to PUs. In [11], the N -th best relay selection method is proposed.…”

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confidence: 99%

“…In [11], the N -th best relay selection method is proposed. However, in spite of the potential of underlay DF cognitive networks, only few works have addressed the BER analysis of these systems [26][27][28][29][30]. Nevertheless, the works in [27][28][29][30] have not investigated the impact of relay selection, which will be shown to be a particularly cumbersome task, even in deriving an approximate BER expression.…”

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confidence: 99%

“…Nevertheless, the works in [27][28][29][30] have not investigated the impact of relay selection, which will be shown to be a particularly cumbersome task, even in deriving an approximate BER expression. It is also noted that the work in [26] studies the effect of relay selection on the BER performance but with a simplified system model, where the relays are assumed geographically close, the source does not interfere with the PU and only interference power constraint is considered. It is recalled here that the OP analysis can provide an insight into the information-theoretic performance limit and motivate practical code designs to reach it.…”

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confidence: 99%

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Bit error rate of underlay decode-and-forward cognitive networks with best relay selection

et al. 2015

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This paper provides an analytic performance evaluation of the bit error rate (BER) of underlay decode-and-forward cognitive networks with best relay selection over Rayleigh multipath fading channels. A generalized BER expression valid for arbitrary operational parameters is firstly presented in the form of a single integral, which is then employed for determining the diversity order and coding gain for different best relay selection scenarios. Furthermore, a novel and highly accurate closed-form approximate BER expression is derived for the specific case where relays are located relatively close to each other. The presented results are rather convenient to handle both analytically and numerically, while they are shown to be in good agreement with results from respective computer simulations. In addition, it is shown that as in the case of conventional relaying networks, the behaviour of underlay relaying cognitive networks with best relay selection depends significantly on the number of involved relays.

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Delay analysis for cognitive radio networks

Halima

Boujemâa

2018

IEEJ Transactions Elec Engng

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In this article, we derive the waiting time and total delay of packets for cooperative cognitive radio networks. In the primary network, there are primary transmitter (PT) and receiver (PR). In the secondary network, there are a source, M relays and a destination. Our results are valid for any number of relays and different relaying protocols: opportunistic amplify and forward (AF), partial AF, reactive AF and reactive DF. The analysis is carried out for nodes with fixed and adaptive transmit power. For fixed transmit power (FTP), we cannot guarantee that interference to PR is less than threshold T. Therefore, some relays are inactive because they generate harmful interference to PR. For adaptive transmit power (ATP), the power of a relay node is fixed so that peak interference power (PIP) or average interference power (AIP) constraints are verified. We also take into account interference from the primary transmitter (PT) by analyzing the delays based on signal to interference plus noise ratio (SINR). © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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Performance analysis of relay selection schemes in underlay cognitive networks with Decode and Forward relaying

Cited by 26 publications

References 12 publications

Performance analysis of cognitive AF relay networks with multiuser switched diversity in Rayleigh fading channels

Performance analysis of cognitive AF relay networks with multiuser switched diversity in Rayleigh fading channels

Bit error rate of underlay decode-and-forward cognitive networks with best relay selection

Delay analysis for cognitive radio networks

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