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Summary: This paper analyzes the performance of a cooperative nonorthogonal multiple access (NOMA) in an underlay cognitive radio network aided by an energy harvesting relay. A secondary source transmits signal for two users, where a near user acts as a relay for the far user. The far user applies the selection combining (SC) approach on the signals which were relayed by the near user and received via direct path from the secondary source. We analytically derive the outage probability (OP) of each user separately, the overall system OP, and the throughput of the system. The impact of the power allocation coefficient of NOMA and energy harvesting parameters on outage is indicated. Further, the performance of the network is investigated with imperfection in successive interference cancellation (SIC), maximal ratio combining (MRC) at relay, and Nakagami‐m fading. The results derived analytically are supported by simulation in MATLAB. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the physical layer security of a hybrid cognitive relay network using an energy harvesting relay in presence of an eavesdropper. In the hybrid scheme, a secondary user (SU) as well as a cognitive relay works either in underlay or in overlay mode. In underlay, the transmit power of the SU as well as the relay is limited by the maximum acceptable interference at primary user (PU) receiver as required by an outage constraint of PU, a quality of service for PU. The secondary network consists of a decode and forward relay that harvests energy from radio frequency signal of secondary transmitter as well as PU transmitter to assist the SU in forwarding the information signal to the destination. A time switching relaying protocol is used at the relay. We evaluate the secrecy outage probability of secondary relay network assuming that channel state information of the interfering links from both the SU and relay transmitter to PU receiver is imperfect. Our results reveal the impact of imperfect channel state information, energy harvesting time, tolerable interference threshold, and PU outage constraint on the secrecy outage probability of SU. [ABSTRACT FROM AUTHOR]

Summary: One of the promising technologies for 5G cellular networks is machine‐to‐machine (M2M) communications. We propose a cognitive radio network (CR) that includes a primary cellular system and a secondary cognitive system. The primary cellular system has a primary client (PC) and the secondary cognitive system has M2M clients which are called secondary clients (SCs). In a conventional system of CR network based on orthogonal frequency division multiple access (CR‐OFDMA), when the primary client (PC) is absent, only one SC can obtain the idle spectrum. But, the SC must leave the spectrum when detecting the existence of the PC. So, the spectrum usage of this system is very low. This paper proposes a cooperative CR network based on nonorthogonal multiple access (CCR‐NOMA) for spectrum sensing using energy detection (ED) to allow multiple SCs to share the same frequency at the same time, but are differentiated according to the power domain or code domain, to improve spectrum efficiency of 5G communications and the transmission performance of CR network at the absence and presence of the PC. To evaluate the channel sensing performance of the ED technique in CCR‐NOMA, we derived a closed‐form expression between the achievable throughput and sensing time for the CCR‐NOMA system. The same analysis for the case of CR‐OFDMA is reproduced for the sake of comparison. The analysis showed that the CR‐NOMA system for M2M communication outperforms the CR‐OFDMA system for M2M communication for the same noncooperative and cooperative spectrum sensing and physical layer parameters. [ABSTRACT FROM AUTHOR]

This paper studies the fairness among the primary users (PUs) and the secondary users (SUs) for resource allocation in cognitive radio systems. We propose a novel co-opetition strategy based on the Kalai-Smorodinsky bargaining solution to balance the system efficiency and the fairness among users. The strategy formulates the spectrum sharing problem as a nonlinear and integral sum utility maximization subject to a set of constraints describing the co-opetition among the PUs and the SUs. Then, we solve the maximization problem by proposing a heuristical method that consists of four steps: multi-PU competition, PU's subcarrier contribution, multi-SU competition, and SU's subcarrier contribution. Extensive simulation results are presented by comparing the co-opetition strategy with several conventional ones, including the Kalai-Smorodinsky bargaining solution, sum rate maximization as well as the Max-Min. Results indicate that the co-opetition strategy can jointly balance the system efficiency and fairness in multiuser resource allocation, as it is able to support more satisfied users and in the meanwhile improve the utility of those unsatisfied. Moreover, the co-opetition can help enable the coexistence of the PUs and the SUs in cognitive radio systems. [ABSTRACT FROM AUTHOR]

SUMMARY: In this paper, resource allocation problem in orthogonal frequency division multiple access‐based cognitive radio (CR) systems to maintain minimum transmission rate constraints of CR users (CRUs) with the specified interference thresholds is investigated. Firstly, a single primary user (PU) CR system is considered, and a suboptimal resource allocation algorithm to maximize the sum transmission rate of all CRUs is proposed. Secondly, the single‐PU scenario is extended to multiple‐PU case, and an asymptotically optimal resource allocation algorithm is proposed using dual methods subject to constraints on both interference thresholds of PUs and total transmit power of all CRUs. Analysis and numerical results show that, in contrast to classical resource allocation algorithms, the proposed algorithm can achieve higher transmission rate and guarantee each CRU's minimum transmission rate in both scenarios. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: Energy resources become precious when the secondary users (SUs) in cognitive radio (CR) network are battery operated, especially in cooperative spectrum sensing (CSS). So it becomes important to use their energy efficiently. In CSS, the number of cooperative users, fusion rule threshold, transmission power, and sensing time affects the energy efficiency (EE) of the CSS. In this paper, an iterative algorithm is proposed to determine joint optimal fusion rule threshold and sensing time that maximizes the EE of CSS. Results show that EE is maximum at optimum sensing duration τs0 = 0.841 ms and fusion rule threshold k0 = 4 at SNR = −18 dB. Maximum EE at optimal point is ξmax = 3.15 bits/Hz/J. Energy resources become precious when the secondary users (SUs) in cognitive radio (CR) network are battery operated, especially in cooperative spectrum sensing (CSS). So it becomes important to use their energy efficiently. In CSS, the number of cooperative users, fusion rule threshold, transmission power, and sensing time affects the energy efficiency (EE) of the CSS. In this paper, an iterative algorithm is proposed to determine joint optimal fusion rule threshold and sensing time that maximizes the EE of CSS. [ABSTRACT FROM AUTHOR]

Summary: The integration of 5G networks with cognitive radio (CR) technology enables the software‐defined networking (SDN) infrastructure to support emergency applications. In future, CR can be integrated with 5G and many wireless networks like Wi‐Fi, WSN, and MANET for efficient spectrum utilization with higher data rate and lower latency. This CR technology allows unlicensed users to access the licensed spectrum, whenever it is free. In this paper, an efficient SDN architecture with cognitive ability for emergency network is proposed in which the SDN controller prolong communication between disaster victims and first responders and so the first responders can arrive at the spot directly and rescue the victims. The SDN controller has cognitive ability so that the victims can utilize the vacant licensed band to communicate with the first responders, thereby improving the spectrum utilization of the network. Another two main challenges during emergency are the occurrence of interference and link failure. The proposed dynamic handover algorithm with interference cancellation (DHAIC) cancels the interference between the nodes inside the network and performs dynamic handoff, whenever link failure occurs between the cluster head (CH) and the controller. An optimum throughput and minimal delay is achieved to ensure the network performance. [ABSTRACT FROM AUTHOR]

Summary: In realistic scenarios of cognitive radio (CR) systems, imperfect channel sensing may occur due to false alarms and miss detections. Channel estimation between the secondary user transmitter and another secondary user receiver is another challenge in CR systems, especially for frequency‐selective fading channels. In this context, this paper presents a study of the effects of imperfect channel sensing and channel estimation on the performance of CR systems. In particular, different methods of channel estimation are analyzed under channel sensing imperfections. Initially, a CR system model with channel sensing errors is described. Then, the expectation maximization (EM) algorithm is implemented in order to learn the channel fading coefficients. By exploiting the pilot symbols and the detected symbols at the secondary user receiver, we can estimate the channel coefficients. We further compare the proposed EM estimation algorithm with different estimation algorithms such as the least squares (LS) and linear minimum mean square error (LMMSE). The expressions of channel estimates and mean squared errors (MSE) are determined, and their dependencies on channel sensing uncertainty are investigated. Finally, to reduce the complexity of EM algorithm, a sub‐optimal algorithm is also proposed. The obtained results show that the proposed sub‐optimal algorithm provides a comparable bit error rate (BER) performance with that of the optimal one yet with less computational complexity. [ABSTRACT FROM AUTHOR]