Cloud Compute-and-Forward with Relay Cooperation

We study a cloud network with M distributed receiving antennas and L users, which transmit their messages towards a centralized decoder (CD), where M>=L. We consider that the cloud network applies the Compute-and-Forward (C&F) protocol, where L antennas/relays are selected to decode integer equations of the transmitted messages. In this work, we focus on the best relay selection and the optimization of the Physical-Layer Network Coding (PNC) at the relays, aiming at the throughput maximization of the network. Existing literature optimizes PNC with respect to the maximization of the minimum rate among users. The proposed strategy maximizes the sum rate of the users allowing nonsymmetric rates, while the optimal solution is explored with the aid of the Pareto frontier. The problem of relay selection is matched to a coalition formation game, where the relays and the CD cooperate in order to maximize their profit. Efficient coalition formation algorithms are proposed, which perform joint relay selection and PNC optimization. Simulation results show that a considerable improvement is achieved compared to existing results, both in terms of the network sum rate and the players' profits.Comment: Submitted to IEEE Transactions on Wireless Communication

Carrier Aggregation for Cooperative Cognitive Radio Networks

The ever-increasing demand for mobile Internet and high-data-rate applications poses unique challenging requirements for 5G mobile networks, including spectrum limitations and massive connectivity. Cognitive radio and carrier aggregation (CA) have recently been proposed as promising technologies to overcome these challenges. In this paper, we investigate joint relay selection and optimal power allocation in an underlay cooperative cognitive radio with CA, taking into account the availability of multiple carrier components in two frequency bands, subject to outage probability requirements for primary users (PUs). The secondary user network employs relay selection, where the relay that maximizes the end-to-end sum rate is selected, assuming both decode-and-forward and amplify-and-forward relaying. The resulting optimization problems are optimally solved using convex optimization tools, i.e., dual decomposition and an efficient iterative method, allowing their application in practical implementations. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom efficiently to maximize the SU rate, while meeting the PU average outage probability constraints. 1 1967-2012 IEEE.Manuscript received May 27, 2016; revised October 2, 2016; accepted November 7, 2016. Date of publication December 2, 2016; date of current version July 14, 2017. The work of P. D. Diamantoulakis, G. K. Karagiannidis, and T. Khattab was supported by the NPRP under Grant NPRP 6-1326-2-532 from the Qatar National Research Fund (a member of Qatar Foundation). This work was presented in part at the IEEE Wireless Communications and Networking Conference (WCNC), Doha, Qatar, Apr. 2016. The review of this paper was coordinated by Prof. D. B. da Costa.Scopu

Underlay cognitive radio : What is the impact of carrier aggregation and relaying on throughput ?

In this paper, we investigate joint relay selection and optimal power allocation, as a means to maximize the achievable rate of an underlay cooperative cognitive radio with carrier aggregation, taking into account the availability of multiple carrier components in two different bands and primary users (PUs) with specific average outage probability requirements. For the acquisition of the interference thresholds, which are set by the PUs on the secondary user (SU), we incorporate a minimum feedback strategy into the problem formulation, based on the minimization of the PUs outage probabilities. The resulting non-convex optimization problem is transformed into a convex one and optimally solved using dual decomposition and an efficient iterative method with closed-form power policies. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom in an efficient way which maximizes the SU throughput while the average outage probability of the PUs is kept at acceptable levels. 2016 IEEE.Scopu

Underlay cognitive radio: What is the impact of carrier aggregation and relaying on throughput?

In this paper, we investigate joint relay selection and optimal power allocation, as a means to maximize the achievable rate of an underlay cooperative cognitive radio with carrier aggregation, taking into account the availability of multiple carrier components in two different bands and primary users (PUs) with specific average outage probability requirements. For the acquisition of the interference thresholds, which are set by the PUs on the secondary user (SU), we incorporate a minimum feedback strategy into the problem formulation, based on the minimization of the PUs outage probabilities. The resulting non-convex optimization problem is transformed into a convex one and optimally solved using dual decomposition and an efficient iterative method with closed-form power policies. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom in an efficient way which maximizes the SU throughput while the average outage probability of the PUs is kept at acceptable levels. 2016 IEEE.Scopus2-s2.0-8498987736

Toward Efficient Integration of Information and Energy Reception

One of the major goals of emerging wireless systems is to prolong the lifetime of wireless communication devices. To this end, this contribution evaluates and optimizes the performance of simultaneous wireless information and power transfer (SWIPT) with an integrated energy and information receiver, which has the advantage of low complexity and energy cost. A tractable expression for the achievable rate is first derived, which is subsequently used to quantify the achievable harvested energy-rate region for the two fundamental SWIPT protocols, namely, power-splitting (PS) and time-switching (TS). In this context, the joint harvested energy-rate outage probability is then defined and minimized for a point-to-point and multicasting system, determining the optimal PS and TS factors for both linear and nonlinear energy harvesting models. In addition, a TS-based broadcasting system is dynamically optimized by maximizing the energy harvested by all users under an achievable rate threshold for each user. The formulated optimization problem is, in fact, particularly challenging due to the non-convex form of the expression for the achievable rate. Yet, an effective solution is ultimately achieved by converting this problem into a convex one. Also, respective computer simulation results corroborate the effectiveness of the proposed framework. Overall, it is shown that the offered results provide meaningful theoretical and practical insights that will be useful in the design and efficient operation of wireless powered systems. Indicatively, unlike the trend in common separated receivers, a region has been identified, where TS outperforms PS.acceptedVersionPeer reviewe