7,739 research outputs found

    Full-Duplex Cooperative Cognitive Radio Networks with Wireless Energy Harvesting

    Full text link
    This paper proposes and analyzes a new full-duplex (FD) cooperative cognitive radio network with wireless energy harvesting (EH). We consider that the secondary receiver is equipped with a FD radio and acts as a FD hybrid access point (HAP), which aims to collect information from its associated EH secondary transmitter (ST) and relay the signals. The ST is assumed to be equipped with an EH unit and a rechargeable battery such that it can harvest and accumulate energy from radio frequency (RF) signals transmitted by the primary transmitter (PT) and the HAP. We develop a novel cooperative spectrum sharing (CSS) protocol for the considered system. In the proposed protocol, thanks to its FD capability, the HAP can receive the PT's signals and transmit energy-bearing signals to charge the ST simultaneously, or forward the PT's signals and receive the ST's signals at the same time. We derive analytical expressions for the achievable throughput of both primary and secondary links by characterizing the dynamic charging/discharging behaviors of the ST battery as a finite-state Markov chain. We present numerical results to validate our theoretical analysis and demonstrate the merits of the proposed protocol over its non-cooperative counterpart.Comment: 6 pages, 3 figures, conferenc

    RF-Powered Cognitive Radio Networks: Technical Challenges and Limitations

    Full text link
    The increasing demand for spectral and energy efficient communication networks has spurred a great interest in energy harvesting (EH) cognitive radio networks (CRNs). Such a revolutionary technology represents a paradigm shift in the development of wireless networks, as it can simultaneously enable the efficient use of the available spectrum and the exploitation of radio frequency (RF) energy in order to reduce the reliance on traditional energy sources. This is mainly triggered by the recent advancements in microelectronics that puts forward RF energy harvesting as a plausible technique in the near future. On the other hand, it is suggested that the operation of a network relying on harvested energy needs to be redesigned to allow the network to reliably function in the long term. To this end, the aim of this survey paper is to provide a comprehensive overview of the recent development and the challenges regarding the operation of CRNs powered by RF energy. In addition, the potential open issues that might be considered for the future research are also discussed in this paper.Comment: 8 pages, 2 figures, 1 table, Accepted in IEEE Communications Magazin

    Resource Allocation in Wireless Networks with RF Energy Harvesting and Transfer

    Full text link
    Radio frequency (RF) energy harvesting and transfer techniques have recently become alternative methods to power the next generation of wireless networks. As this emerging technology enables proactive replenishment of wireless devices, it is advantageous in supporting applications with quality-of-service (QoS) requirement. This article focuses on the resource allocation issues in wireless networks with RF energy harvesting capability, referred to as RF energy harvesting networks (RF-EHNs). First, we present an overview of the RF-EHNs, followed by a review of a variety of issues regarding resource allocation. Then, we present a case study of designing in the receiver operation policy, which is of paramount importance in the RF-EHNs. We focus on QoS support and service differentiation, which have not been addressed by previous literatures. Furthermore, we outline some open research directions.Comment: To appear in IEEE Networ

    Optimal Cooperative Cognitive Relaying and Spectrum Access for an Energy Harvesting Cognitive Radio: Reinforcement Learning Approach

    Full text link
    In this paper, we consider a cognitive setting under the context of cooperative communications, where the cognitive radio (CR) user is assumed to be a self-organized relay for the network. The CR user and the PU are assumed to be energy harvesters. The CR user cooperatively relays some of the undelivered packets of the primary user (PU). Specifically, the CR user stores a fraction of the undelivered primary packets in a relaying queue (buffer). It manages the flow of the undelivered primary packets to its relaying queue using the appropriate actions over time slots. Moreover, it has the decision of choosing the used queue for channel accessing at idle time slots (slots where the PU's queue is empty). It is assumed that one data packet transmission dissipates one energy packet. The optimal policy changes according to the primary and CR users arrival rates to the data and energy queues as well as the channels connectivity. The CR user saves energy for the PU by taking the responsibility of relaying the undelivered primary packets. It optimally organizes its own energy packets to maximize its payoff as time progresses

    Sensing Throughput Optimization in Fading Cognitive Multiple Access Channels With Energy Harvesting Secondary Transmitters

    Get PDF
    The paper investigates the problem of maximizing expected sum throughput in a fading multiple access cognitive radio network when secondary user (SU) transmitters have energy harvesting capability, and perform cooperative spectrum sensing. We formulate the problem as maximization of sum-capacity of the cognitive multiple access network over a finite time horizon subject to a time averaged interference constraint at the primary user (PU) and almost sure energy causality constraints at the SUs. The problem is a mixed integer non-linear program with respect to two decision variables namely spectrum access decision and spectrum sensing decision, and the continuous variables sensing time and transmission power. In general, this problem is known to be NP hard. For optimization over these two decision variables, we use an exhaustive search policy when the length of the time horizon is small, and a heuristic policy for longer horizons. For given values of the decision variables, the problem simplifies into a joint optimization on SU \textit{transmission power} and \textit{sensing time}, which is non-convex in nature. We solve the resulting optimization problem as an alternating convex optimization problem for both non-causal and causal channel state information and harvested energy information patterns at the SU base station (SBS) or fusion center (FC). We present an analytic solution for the non-causal scenario with infinite battery capacity for a general finite horizon problem.We formulate the problem with causal information and finite battery capacity as a stochastic control problem and solve it using the technique of dynamic programming. Numerical results are presented to illustrate the performance of the various algorithms
    • …
    corecore