Elsevier

Computer Networks

Volume 166, 15 January 2020, 106974
Computer Networks

Buffer-aided cooperative spectrum sharing with full-duplex wireless-powered relay

https://doi.org/10.1016/j.comnet.2019.106974Get rights and content

Abstract

A buffer-aided wireless energy harvesting and information transfer protocol is proposed for full-duplex cooperative cognitive radio networks. In particular, during a transmission block, a secondary transmitter (ST) as a full-duplex relay first scavenges dedicated radio frequency (RF) energy signal transmitting from primary transmitter (PT), and then assists to transmit primary signals by using the harvested energy in exchange for the opportunity of spectrum sharing, where the primary and secondary signals are combined linearly. A buffer with limited-size is implemented on the ST and secondary receiver (SR) to storage the decoded current primary data. The SR performs successive interference decoding and cancelation to obtain desired secondary signal. The primary receiver (PR) detects the desired primary signal by treating the secondary signal as interference. Based on this, the closed-form expressions of the exact outage probabilities for both the primary and secondary systems are derived. Optimal energy harvesting duration and power allocation factor are determined by maximizing the achievable throughput of secondary system while maintaining the transmission performance of the primary system. Simulation results demonstrate that the proposed scheme achieves effective primary transmission while provides a superior transmission performance for the secondary system.

Introduction

With the rapid increase and development of the wireless devices and services, the next generation mobile communication technologies are excepted to provide high capacity and low energy consumption transmission services [1], [2]. In the meanwhile, conventional spectrum management strategy also leads that spectrum resources are under utilized for most of the time [3], [4]. Therefore, how to effectively implement these new wireless services and applications under the constraint of limited radio spectrum is becoming an extremely challenge at present. Cognitive radio (CR) technologies have been recognized as a promising method to solve the shortage of spectrum resources, where the secondary users (SUs) can be allowed opportunistically to access the licence spectrum for data transmission, which is also known as dynamic spectrum access (DSA) [5], [6], [7].

Energy scarcity is another critical factor affecting the development of wireless communications, especially for sensors and cellular networks, which are generally powered by batteries and they are difficult to be replaced by new ones. To solve this problem, wireless-powered technology has been paid high attention since the devices can be able to scavenge energy from the surrounding environment into electric energy for future data transmission, such as solar, wind or RF signals [8]. Especially with the concurrent developments in design of antennas and circuits, wireless energy harvesting based on RF signal is more attractive due to its wireless, low cost, and small form factor implementation [9], [10], [11]. Although the amount of harvested energy is in milli-watts, it is sufficient for powering low-power wireless sensors. Therefore, the combination of cognitive radio networks with energy harvesting can effectively improve both the spectral efficiency and energy efficiency.

To full utilize the potential gain of wireless energy harvesting, simultaneous wireless information and power transmission (SWIPT) scheme is developed in wireless networks, where the RF signals can be used to transfer both the energy and information to receiver. The architecture designs with time-switching (TS) protocol and power-splitting (PS) protocol for allowing SWIPT at the receiver side were presented in [12], [13]. For point-to-point wireless systems, a suitable SWIPT scheme was proposed for single-input single-output (SISO) fading channel [14]. In [15], SWIPT has been investigated in multiple-input single-output (MISO) systems, where a transmitter was equipped multi-antenna and each single-antenna receiver can be able to obtain energy and information simultaneously by utilizing TS circuit. Moreover, the PS-based SWIPT scheme was investigated in MISO multicasting systems [16]. In [17], the authors applied the SWIPT in relay interference channels for multiple source-destination pairs communication system, where each pair of link has a dedicated energy harvesting relay serving for relaying transmission. Then, optimal power splitting ratios for all relays were derived by utilizing the distributed power splitting framework with game theory.

In the context of cognitive radio networks, the energy harvesting technologies have been investigated in the literatures recently [18], [19], [20], [21], [22]. A CR system with energy harvesting was analyzed in [18], where the CR system scavenged the energy from the RF signals sending from the primary user during sensing time and transmission time of a detection cycle when the PU is present. In [19], the authors investigated the maximum achievable throughput of an energy-harvesting-based multiuser CR network with different sensing probabilities, channel access probabilities, and energy queue capacities. Considering a wireless-powered CR network, the authors of [20] proposed an optimal cooperative transmission strategy to maximize the achievable throughput of the secondary system. For large-scale CR networks, the authors of [21] developed an underlaid spectrum sharing scheme and derived the exact expression of the primary transmission probability by using discrete-time energy harvesting model. In [22], an energy threshold based on multi-relay selection scheme was proposed for cooperative relaying network with accumulate-then-forward energy harvesting relay. Then, the approximate analytical expressions of system outage probability with different channel types were derived.

In the previous works [18], [19], [20], [21], [22], the relay nodes of the secondary system were only operated in half-duplex (HD) mode, where the node transmits and receives data in the orthogonal frequency or time resource. However, one of the most significant disadvantages of half-duplex (FD) transmission is that the data reception and transmission occurs at different transmission-slots, which will result in a lot of multiplexing loss for relay node. The bandwidth loss in traditional HD relaying mode can be compensated in FD relaying mode since the relay node can concurrently transmit and receive data over the same frequency band, which also brings coupling of strong transmitting data into the receiver path, i.e., loop-interference (LI). Thus, a lot of researches were focused on LI mitigation in FD-based communications [23], [24]. Applying the FD relaying in CR networks, the SUs can simultaneously sense the idle channel and transmit data, which can extremely improve the spectrum efficiency. A novel cooperative CR network was considered with FD-based relay nodes, which can wirelessly charge for the ST and receiving PT’s signal simultaneously in the first phase, and then perform decode-and-forward (DF) to relay the decoded primary signal in the following transmission phase [25]. El-Malek et al. [26] investigated a FD-based CR network comprised of multiple SUs, which can scavenge energy from a hybrid base station and PU’s downlink and uplink transmissions. Then, an optimal user selection strategy was proposed in SU system to achieve a higher throughput. A minimum transmission protocol for bi-node FD-bases systems with energy harvesting was developed, where two types of energy harvesting and information schemes were proposed for improving both energy and spectrum efficiencies [27].

In this paper, we propose a novel spectrum sharing scheme in an overlaid CR network with wireless-powered FD relaying. Specifically, a FD-enabled ST can scavenge energy from the PT’s dedicated signals in the first phase, and then receives and stores the current primary signal while transmits the previous primary signal and current secondary signal in the second phase. In above mentioned references [25], [26], the SR in transmission models can actually receive the primary signal during the PT’s transmission phase, which will result in an interference for SR to derive its desired signal. Therefore, we assume that the SR also implements a limited-size buffer, which can be utilized to store the current primary signal for performing the successive interference cancelation in next transmission-slot. Furthermore, we consider a successively cognitive transmission model in this paper, where the energy harvesting and data transmission will occur in each transmission-slot. However, if the non-linear energy harvesting mode is adopted in the proposed model, any given transmission-slot will either only use for harvesting energy or transmitting data. Thus, adopting linear energy harvesting mode is much more suitable for the considered transmission protocol. The main contributions of this work are summarized as follows:

  • We develop a spectrum sharing scheme for overlay CR network with wireless-powered FD relaying. In particular, a buffer-aided ST acts as a FD relay to harvest energy first and then help the primary transmission in a successive fashion. Meanwhile, the ST also transmits its own data to the intended SR, where the previous primary signal and the current signal are linearly combined by utilizing superposition coding strategy. The SR performs successive interference decoding and cancelation to obtain desired secondary signal, the current primary signal is also stored in a buffer with limited-size for interference cancelation in next transmission-slot. In order to extract the primary signal, maximal ratio combining (MRC) is adopted at the PR by treating the secondary signal as interference.

  • We derive analytical expressions of the outage probabilities for both the primary and secondary systems, which are also validated by Monte-Carlo simulations. The optimal energy harvesting duration and power allocation factor are determined by maximizing the achievable throughput of the secondary system while guaranteeing the primary achievable throughput, a corresponding optimal algorithm is then proposed.

  • We provide the numerical results which reveal the impact of system transmission performance with various system parameters, e.g. power allocation coefficient, transmission power of the primary system, and transmission distance. Besides, the derived performance expressions offer a practical guideline that the proposed spectrum sharing scheme with optimal parameters can achieve a higher secondary achievable throughput with the optimal coefficients than other scheme.

The remainder of this paper is organized as follows. In Section 2, the system model is introduced and the spectrum sharing scheme based on wireless powered FD relaying for CR networks is proposed. Section 3 analyzes the outage probabilities for both the primary and secondary systems. Besides, an algorithm to derive the optimal energy harvesting duration and power allocation factor is given in Section 4. Simulation and numerical results are presented in Section 5. Finally, Section 6 concludes this paper.

Section snippets

System model

As shown in Fig. 1, we consider a cooperative cognitive radio network (CCRN) with full-duplex (FD) relay, where a PT and a ST intend to deliver their data to a primary receiver (PR) and a SR, respectively. Consider a scenario that the direct channel between the PT and PR is in outage due to large propagation loss and physical obstacles. The PR is assumed to be located within the transmission range of ST, the FD-based ST thus can act as a relay to assist the primary transmission. In return, the

Outage probability analysis

Based on the proposed transmission protocol, at the time-slot m+1, the spectrum sharing is performed only when the previous primary signal xP,m is decoded correctly at ST. From (6), in order to detect xP,m correctly, the given target secondary transmission rate rP should not be larger than the achievable rate RST,m, which is given byRST,m=(1α)Tlog2(1+PP|hPST|2PST|hLI|2+δ2).Therefore, the spectrum sharing probability, i.e., the probability of successful decoding xP,m at the ST, is written asPr{S

Optimization problem analysis with Pareto boundary

For the proposed spectrum sharing schemes, the transmission opportunity for the secondary system will be lower if the primary system requests a higher transmission rate. In order to achieve mutual interests for both the primary and secondary systems, we aim to maximize the data rate of the SR while guaranteeing transmission rate of PR is large than or equal to a given threshold. We define achievable rate region (RP,RS) to characterize the rates that can be simultaneously achieved by the primary

Numerical and simulation results

In this section, we will present the numerical results to verify the accuracy of the theoretical analyses in Section 3 with Monte Carlo simulations. Considering the large-scale fading, the mean of channel power gain is λi=diθ, where di denotes transmission distance and θ=3 being the path loss exponent. In the simulations, we set the power of noise δ2=30dBm and the mean of power gain |hLI|2=10dBm. The distance between any two nodes are set as dPST=dPSR=5 m, dSPR=(10dPST)m, and dSS=3.5 m. The

Conclusion

In this paper, we propose a buffer-aided wireless energy harvesting and information transfer protocol for full-duplex cooperative cognitive radio networks, where the secondary transmitter as full-duplex relay first harvests RF energy and then performing cognitive transmission to send the primary and secondary signals simultaneously. The SR applies successive interference decoding and cancelation scheme to obtain the desired secondary signal and current primary for interference cancelation in

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors thank the Project funded by China Postdoctoral Science Foundation under Grant no. 2019M652895, in part by the Research Foundation of Education Department of Hunan Province under Grant no. 18B517, in part by the National Science Foundation of China under Grant 61871189, and in part by the Guangdong Innovative and Entrepreneurial Research Team Program under Grant 2017ZT07X032.

Kun Tang received the B.S. degree in telecommunications from Wuhan University of Technology, Wuhan, China, in 2006, and M.S. degree in The University of New South Wales, Sydney, Australia, in 2011, and Ph.D. degree in Telecommunications from the Central South University, Changsha, China, in 2018. He is now a postdoctor with the school of Electronic and Information at South China University of Technology. His research interests are in the areas of cognitive radio networks, sensor networks and

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  • Cited by (0)

    Kun Tang received the B.S. degree in telecommunications from Wuhan University of Technology, Wuhan, China, in 2006, and M.S. degree in The University of New South Wales, Sydney, Australia, in 2011, and Ph.D. degree in Telecommunications from the Central South University, Changsha, China, in 2018. He is now a postdoctor with the school of Electronic and Information at South China University of Technology. His research interests are in the areas of cognitive radio networks, sensor networks and Massive MIMO.

    Shaowei Liao received the Ph.D. degree in electromagnetic fields and microwave technology from the University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2010. In 2011, he joined the School of Electronic Engineering, UESTC, as a Lecturer. From 2011 to 2012, he was a Senior Research Associate with the Department of Electronic Engineering, City University of Hong Kong, Hong Kong. From 2012 to 2013, he was a Research Scientist with Bell Labs Research, Shanghai, China, Shanghai Bell, Shanghai, and Alcatel-Lucent, Shanghai. From 2013 to 2017, he was an Engineer with the State Key Laboratory of Millimeter Waves, City University of Hong Kong. He is currently an Associate Professor with the School of Electronics and Information Engineering, South China University of Technology, Guangzhou, China. He has authored or coauthored more than 30 papers on IEEE journals. He holds five granted U.S. and European patents. His current research interests include various antennas, microwave components, and computational electromagnetics. Dr. Liao was a recipient of the 2017 H. A. Wheeler Applications Prize Paper Award. He is the reviewer for the IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, and IEEE MICROWAVE AND WIRELESS COMPONENTS LETTERS.

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