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In this paper, we consider the channel allocation problem for throughput maximization in cognitive radio networks with hardware-constrained secondary users. Specifically, we assume that secondary users (SUs) exploit spectrum holes on a set of channels where each SU can use at most one available channel for communication. We present the optimal brute-force search algorithm and its complexity for this non-linear integer optimization problem. Since the optimal solution has exponential complexity with the numbers of channels and SUs, we develop two low-complexity channel assignment algorithms that can efficiently utilize spectrum opportunities on these channels. In the first algorithm, SUs are assigned distinct sets of channels. We show that this algorithm achieves the maximum throughput limit if the number of channels is sufficiently large. In addition, we propose an overlapping channel assignment algorithm, that can improve the throughput performance compared to the nonoverlapping channel assignment counterpart. In addition, we design a distributed MAC protocol for access contention resolution and integrate it into the overlapping channel assignment algorithm. We also analyze the saturation throughput and the complexity of the proposed channel assignment algorithms. Moreover, we have presented several potential extensions including greedy channel assignment algorithms under max-min fairness criterion and throughput analysis considering sensing errors. Finally, numerical results are presented to validate the developed theoretical results and illustrate the performance gains due to the proposed channel assignment algorithms. Index TermsChannel assignment, MAC protocol, spectrum sensing, throughput maximization, cognitive radio. I. INTRODUCTIONEmerging broadband wireless applications have been demanding unprecedented increase in radio spectrum resources. As a result, we have been facing a serious spectrum shortage problem. However, several recent measurements reveal very low spectrum utilization in most useful frequency bands [1]. Cognitive radio technology is a promising technology that can fundamentally improve the spectrum utilization of licensed frequency bands through secondary spectrum access. However, transmissions from primary users (PUs) should be satisfactorily protected from secondary spectrum access due to their strictly higher access priority.Protection of primary communications can be achieved through interference avoidance or interference control approach (i.e., spectrum overlay or spectrum underlay) [1]. For the interference control approach, transmission powers of SUs should be carefully controlled so that the aggregated interference they create at primary receivers does not severely affect ongoing primary communications [2]. In most practical scenarios where direct coordination between PUs and SUs is not possible and/or if distributed communications strategies are desired, it would be very difficult to maintain these interference constraints. The interference avoidance approach instead prote...

In this paper, we propose a joint communication, caching and computing strategy for achieving cost efficiency in vehicular networks. In particular, the resource allocation policy is specifically designed by considering the vehicle's mobility and the hard service deadline constraint. An artificial intelligencebased multi-timescale framework is proposed for tackling these challenges. To mitigate the complexity associated with this large action and search space in the sophisticated multi-timescale framework considered, we propose to maximize a carefully constructed mobility-aware reward function using the classic particle swarm optimization scheme at the associated large timescale level, while we employ deep reinforcement learning at the small timescale level of our sophisticated twin-timescale solution. Numerical results are presented to illustrate the theoretical findings and to quantify the performance gains attained.

Abstract-Body-coupled communications (BCC), in which the human body is used as a communications channel, has been shown to be a promising solution for wireless body-area networks (WBANs). For successful deployment of these BCC-based WBANs, it is necessary to develop a clear understanding of the channel behavior. Therefore, this paper presents the key characteristics of the capacitively-coupled on-body channel used for BCC. This is based on an experimental study, which was carried out with a specifically designed measurement system. The goal of the study was to reveal the influence of electrode design, electrode position and body motion on the propagation loss and to characterize the experienced interference. It is concluded that the maximum propagation loss for the whole body channel is below 80 dB. Moreover, the frequency dispersion and the influence of body movement on channel attenuation are shown to be much smaller than for radio frequency (RF) WBAN channels. From the results we conclude that BCC can result in a simpler, more robust, and lower-power WBAN than what is achievable with traditional RF solutions.

In this paper, we investigate the joint optimal sensing and distributed MAC protocol design problem for cognitive radio networks. We consider both scenarios with single and multiple channels. For each scenario, we design a synchronized MAC protocol for dynamic spectrum sharing among multiple secondary users, which incorporates spectrum sensing for protecting active primary users. We perform saturation throughput analysis for the corresponding proposed MAC protocols that explicitly capture spectrum sensing performance. Then, we find their optimal configuration by formulating throughput maximization problems subject to detection probability constraints for primary users. In particular, the optimal solution of the optimization problem returns the required sensing time for primary users' protection and optimal contention window for maximizing total throughput of the secondary network. Finally, numerical results are presented to illustrate developed theoretical findings in the paper and significant performance gains of the optimal sensing and protocol configuration.

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In this paper, we propose a semi-distributed cooperative spectrum sensing (SDCSS) and channel access framework for multi-channel cognitive radio networks (CRNs). In particular, we consider a SDCSS scheme where secondary users (SUs) perform sensing and exchange sensing outcomes with each other to locate spectrum holes. In addition, we devise the p-persistent CSMA-based cognitive medium access control (MAC) protocol integrating the SDCSS to enable efficient spectrum sharing among SUs. We then perform throughput analysis and develop an algorithm to determine the spectrum sensing and access parameters to maximize the throughput for a given allocation of channel sensing sets. Moreover, we consider the spectrum sensing set optimization problem for SUs to maximize the overall system throughput. We present both exhaustive search and low-complexity greedy algorithms to determine the sensing sets for SUs and analyze their complexity. We also show how our design and analysis can be extended to consider reporting errors. Finally, extensive numerical results are presented to demonstrate the significant performance gain of our optimized design framework with respect to non-optimized designs as well as the impacts of different protocol parameters on the throughput performance.

In this paper, we propose an adaptive Medium Access Control (MAC) protocol for full-duplex (FD) cognitive radio networks in which FD secondary users (SUs) perform channel contention followed by concurrent spectrum sensing and transmission, and transmission only with maximum power in two different stages (called the FD sensing and transmission stages, respectively) in each contention and access cycle. The proposed FD cognitive MAC (FDC-MAC) protocol does not require synchronization among SUs and it efficiently utilizes the spectrum and mitigates the self-interference in the FD transceiver. We then develop a mathematical model to analyze the throughput performance of the FDC-MAC protocol where both half-duplex (HD) transmission (HDTx) and FD transmission (FDTx) modes are considered in the transmission stage. Then, we study the FDC-MAC configuration optimization through adaptively controlling the spectrum sensing duration and transmit power level in the FD sensing stage where we prove that there exists optimal sensing time and transmit power to achieve the maximum throughput and we develop an algorithm to configure the proposed FDC-MAC protocol. Extensive numerical results are presented to illustrate the characteristic of the optimal FDC-MAC configuration and the impacts of protocol parameters and the self-interference cancellation quality on the throughput performance. Moreover, we demonstrate the significant throughput gains of the FDC-MAC protocol with respect to existing half-duplex MAC (HD MAC) and single-stage FD MAC protocols.Index Terms-General asynchronous MAC, full-duplex MAC, full-duplex spectrum sensing, optimal sensing duration, throughput maximization, self-interference control, full-duplex cognitive radios, throughput analysis. He is currently a Postdoctoral Research Associate atÉcole Polytechnique de Montréal, Canada. Before that he worked as a lecturer at Ho Chi Minh City University of Technical Education from 2002 to 2010. His current research activities focus on internet of things (IOT over LTE/LTE-A network, cyber-physical systems, big data, distributed sensing and control), time series analysis and dynamic factor models (stationary and non-stationary), wireless communications and networking, Cloud-RAN, cognitive radios (software defined radio architectures, protocol design, spectrum sensing, detection, and estimation), statistical signal processing, random matrix theory, compressed sensing, and compressed sampling. He has served on TPCs of different international conferences including IEEE CROWNCOM, VTC, PIMRC, etc. He is a Member of the IEEE.Long Le (S'04-M'07-SM'12) received the B.Eng.