Optimal harvesting and sensing durations for cognitive radio networks
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ORIGINAL PAPER
Optimal harvesting and sensing durations for cognitive radio networks Raed Alhamad1 · Hatem Boujemâa2 Received: 27 September 2019 / Revised: 13 February 2020 / Accepted: 29 March 2020 © Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract In this paper, we optimize both harvesting and sensing durations for cognitive radio networks (CRNs). There are a primary source and destination PS and PD . In the secondary network, there are a secondary source and destination SS and S D . There are three time slots in secondary network. In the first one, secondary source SS harvests energy from radio frequency (RF) signal received from another node A. Node A can be a base station or any other node transmitting RF signal. In the second time slot, secondary source senses the channel using the energy detector to detect primary source activity. When PS is idle, the secondary source transmits data to secondary destination S D in the last time slot. We optimize harvesting and sensing durations to maximize the throughput. Our results are valid for quadrature amplitude modulation (QAM), phase shift keying (PSK) and amplitude shift keying (ASK) in the presence of Rayleigh or Nakagami fading channels. Keywords Energy harvesting · Spectrum sensing · Throughput analysis and optimization
1 Introduction In energy harvesting systems, wireless nodes harvest energy from different sources of energy such as solar, wind or radio frequency (RF) signals [1–5]. Energy harvesting allows to increase battery’s lifetime and reduce power consumption. The harvested energy is mainly used to transmit data in wireless systems. Relaying techniques have been extensively studied for energy harvesting systems [6–9]. Relay nodes can help the secondary source to deliver its packet using amplify and forward (AF) or decode and forward (DF) relaying. Several relay selection techniques were studied, such as opportunistic relaying, partial or reactive relay selection [6,8]. Energy harvesting has been also applied in two-way relaying where two source nodes exchange data simultaneously using relay nodes [10,11]. Optimal power allocation techniques for energy harvesting systems were suggested in [12–16]. Optimal power allocation consists to adjust the power of nodes using the distance between the transmitter and
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Raed Alhamad [email protected] Hatem Boujemâa [email protected]
1
Department of Computer Science, College of Computation and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia
2
COSIM Lab, Tunis, Tunisia
receiver. The adaption can be made using either the instantaneous or average channel gains [12]. In cognitive radio networks (CRNs), secondary source should sense the channel and is allowed to opportunistically transmit only when primary source is idle [17–20]. CRN allows to improve the usage of frequency bands, but it requires to sense the channel to avoid to generate a lot of interference to primary users. In [21], the throughput of CRN with imperfect sensing was analyzed in the presence of bursty traff
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