This paper considers the application of non-orthogonal multiple access (NOMA) into cooperative cognitive radio (CR) networks with simultaneous wireless information and power transfer (SWIPT). For NOMA in cooperative CR networks with SWIPT, the cognitive relay harvests the transmission power from the secondary transmitter with power splitting scheme, while the fixed power allocation scheme is used for the NOMA protocol. The closed-form analytical expression of the overall outage probability for the proposed networks is derived, as well as its diversity order at high signal-to-noise ratio (SNR) region is investigated. Furthermore, compared to OMA in cooperative CR networks with SWIPT, the proposed scheme can always achieve the same diversity order, but lower overall outage performance. Compared with NOMA in cooperative CR networks using its own battery for transmission, the SWIPT NOMA in cooperative CR networks will lead to losing a little of the overall outage performance, but without losing the diversity order. INDEX TERMS Non-orthogonal multiple access, cognitive radio network, decode-and-forward, simultaneous wireless information and power transfer, outage probability, diversity gain.
In this paper, the performance of a dual-hop multiuser underlay cognitive network is thoroughly investigated by using decode-and-forward (DF) protocol at the relay node and employing opportunistic scheduling at the destination users. A practical scenario where co-channel interference (CCI) signals are present in the system is considered for the investigation. Considering that transmissions are performed over non-identical Rayleigh fading channels, first, the exact signal-to-interferenceplus-noise ratio (SINR) of the network is formulated. Then, the exact equivalent cumulative distribution function (CDF) and the outage probability of the system SINR are derived. An efficient tight approximation is proposed for the per hop CDFs, based on which, the closed-form expressions for the error probability and the ergodic capacity are derived. Furthermore, an asymptotic expression for the CDF of the instantaneous SINR is derived; and a simple and general asymptotic expression for the error probability is presented and discussed. Moreover, the adaptive power allocation under total transmit power constraint is studied in order to minimize the asymptotic average error probability. As expected, the results show that optimum power allocation improves the system performance compared with the uniform power allocation. Finally, the theoretical analysis is validated by presenting various numerical results and Monte Carlo simulations. Index Terms-Underlay cognitive radio, dual-hop decodeand-forward, co-channel interference, error probability, outage probability, ergodic capacity, optimization I. INTRODUCTION C OGNITIVE radio (CR) has become a more attractive research field in wireless communication for many researchers in the last few years [1]-[5]. This is because of its promise of using the existing frequency spectrum more efficiently. Recently, three paradigms have been proposed for realizing the CR network [2]. Based on the simplicity of implementation, they are underlay, interweave and overlay. In an underlay CR scheme, there is a strict power constraint on the transmission power [2] for the purpose of the protection of the quality of service (QoS) of the primary user. One of
This letter investigates a multiple-input singleoutput (MISO) secrecy channel, where the legitimate user and the eavesdroppers employ power splitting (PS) scheme for information decoding (ID) and energy harvesting (EH), simultaneously. An artificial noise (AN) is embedded the information bearing signal to interfere the eavesdroppers, and to harvest power by all receivers (i.e., legitimate user and eavesdroppers). We consider the robust secrecy rate maximization problem subject to the transmit power and the EH constraints by incorporating normbounded channel uncertainty. This robust optimization problem is not convex, thus, it can be reformulated as a convex one along with matrix transformations and convex conic optimization techniques, which is solved iteratively based on constrained concaveconvex procedure (CCCP) based algorithm. Finally, numerical results are provided to validate our proposed algorithm.
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