scholarly journals Exploiting Sparsity in Amplify-and-Forward Broadband Multiple Relay Selection

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 57985-57995
Author(s):  
Ala Gouissem ◽  
Ridha Hamila ◽  
Naofal Al-dhahir ◽  
Sebti Foufou
2019 ◽  
Vol 13 (2) ◽  
pp. 1534-1545 ◽  
Author(s):  
Ala Gouissem ◽  
Lutfi Samara ◽  
Ridha Hamila ◽  
Naofal Al-Dhahir ◽  
Sebti Foufou

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Kiran Sultan ◽  
Ijaz Mansoor Qureshi ◽  
Aqdas Naveed Malik ◽  
Muhammad Zubair

Cooperative communication is regarded as a key technology in wireless networks, including cognitive radio networks (CRNs), which increases the diversity order of the signal to combat the unfavorable effects of the fading channels, by allowing distributed terminals to collaborate through sophisticated signal processing. Underlay CRNs have strict interference constraints towards the secondary users (SUs) active in the frequency band of the primary users (PUs), which limits their transmit power and their coverage area. Relay selection offers a potential solution to the challenges faced by underlay networks, by selecting either single best relay or a subset of potential relay set under different design requirements and assumptions. The best relay selection schemes proposed in the literature for amplify-and-forward (AF) based underlay cognitive relay networks have been very well studied in terms of outage probability (OP) and bit error rate (BER), which is deficient in multiple relay selection schemes. The novelty of this work is to study the outage behavior of multiple relay selection in the underlay CRN and derive the closed-form expressions for the OP and BER through cumulative distribution function (CDF) of the SNR received at the destination. The effectiveness of relay subset selection is shown through simulation results.


2019 ◽  
Vol 10 (3) ◽  
pp. 1-18 ◽  
Author(s):  
Kiran Sultan ◽  
Ijaz Mansoor Qureshi ◽  
Muhammad Atta-ur Rahman ◽  
Bassam A. Zafar ◽  
Muhammad Zaheer

In this article, a multiple relay selection (MRS) scheme for signal-to-noise ratio (SNR) enhancement is proposed for underlay relay-assisted cognitive radio networks (RCRNs). A secondary source-destination pair experiencing deep fading on direct path is assisted by amplify-and-forward (AF) relays in an underlay mode. In this energy-constrained scenario, the aim is to maximize the secondary network's end-to-end SNR through an intelligent power-saving method incorporated with MRS. In contrast to the prior relay selection (RS) schemes, the relay-selection factor is the difference of SNR of the source-relay link and corresponding relay-destination link for each relay along with its corresponding interference channel coefficient. The difference factor aims to achieve the SNR upper bound while performing minimum power amplification, eventually resulting in interference mitigation as well. The proposed algorithm has been implemented using Fuzzy Rule Based System (FRBS), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and their performance has been compared through simulations.


2014 ◽  
Vol 513-517 ◽  
pp. 3423-3428
Author(s):  
Zhi Kang Zhou ◽  
Qi Zhu

In this paper, an amplify-and-forward (AF) multi-relay network is considered. In order to minimize the system outage probability, a new power allocation and multi-relay selection algorithm is proposed under total power constraint and each node power constraint. In the proposed algorithm, the ideal of ordering is adopted, which leads to the remarkable decrease of the computation complexity together with simple power reallocation. Simulation results show that the proposed multi-relay selection algorithm performs close to the optimal scheme with optimal power allocation and exhaustive search (OPA-ES) but with much lower complexity.


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