Spectrum-Aware and Energy-Adaptive Reliable Transport for Internet of Sensing Things

© 1967-2012 IEEE. Wireless sensors equipped with cognitive radio, i.e., cognitive radio sensor networks (CRSN), can access the spectrum in an opportunistic manner and coexist with licensed users to mitigate the crowded spectrum problem and provide ubiquitous remote event monitoring and tracking for cyber-physical systems. In this paper, a novel transport layer protocol for CRSN, spectrum-aware energy-adaptive reliable transport protocol is presented to enable energy-adaptive collaborative event sensing in spectrum-scarce cyber-physical systems. To the best of our knowledge, this is the first attempt to specifically devise a reliable event transport scheme for CRSN

Design and Analysis of Opportunistic MAC Protocols for Cognitive Radio Wireless Networks

As more and more wireless applications/services emerge in the market, the already heavily crowded radio spectrum becomes much scarcer. Meanwhile, however,as it is reported in the recent literature, there is a large amount of radio spectrum that is under-utilized. This motivates the concept of cognitive radio wireless networks that allow the unlicensed secondary-users (SUs) to dynamically use the vacant radio spectrum which is not being used by the licensed primary-users (PUs). In this dissertation, we investigate protocol design for both the synchronous and asynchronous cognitive radio networks with emphasis on the medium access control (MAC) layer. We propose various spectrum sharing schemes, opportunistic packet scheduling schemes, and spectrum sensing schemes in the MAC and physical (PHY) layers for different types of cognitive radio networks, allowing the SUs to opportunistically utilize the licensed spectrum while confining the level of interference to the range the PUs can tolerate. First, we propose the cross-layer based multi-channel MAC protocol, which integrates the cooperative spectrum sensing at PHY layer and the interweave-based spectrum access at MAC layer, for the synchronous cognitive radio networks. Second, we propose the channel-hopping based single-transceiver MAC protocol for the hardware-constrained synchronous cognitive radio networks, under which the SUs can identify and exploit the vacant channels by dynamically switching across the licensed channels with their distinct channel-hopping sequences. Third, we propose the opportunistic multi-channel MAC protocol with the two-threshold sequential spectrum sensing algorithm for asynchronous cognitive radio networks. Fourth, by combining the interweave and underlay spectrum sharing modes, we propose the adaptive spectrum sharing scheme for code division multiple access (CDMA) based cognitive MAC in the uplink communications over the asynchronous cognitive radio networks, where the PUs may have different types of channel usage patterns. Finally, we develop a packet scheduling scheme for the PU MAC protocol in the context of time division multiple access (TDMA)-based cognitive radio wireless networks, which is designed to operate friendly towards the SUs in terms of the vacant-channel probability. We also develop various analytical models, including the Markov chain models, M=GY =1 queuing models, cross-layer optimization models, etc., to rigorously analyze the performance of our proposed MAC protocols in terms of aggregate throughput, access delay, and packet drop rate for both the saturation network case and non-saturation network case. In addition, we conducted extensive simulations to validate our analytical models and evaluate our proposed MAC protocols/schemes. Both the numerical and simulation results show that our proposed MAC protocols/schemes can significantly improve the spectrum utilization efficiency of wireless networks

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe

Joint Channel Assignment and Opportunistic Routing for Maximizing Throughput in Cognitive Radio Networks

In this paper, we consider the joint opportunistic routing and channel assignment problem in multi-channel multi-radio (MCMR) cognitive radio networks (CRNs) for improving aggregate throughput of the secondary users. We first present the nonlinear programming optimization model for this joint problem, taking into account the feature of CRNs-channel uncertainty. Then considering the queue state of a node, we propose a new scheme to select proper forwarding candidates for opportunistic routing. Furthermore, a new algorithm for calculating the forwarding probability of any packet at a node is proposed, which is used to calculate how many packets a forwarder should send, so that the duplicate transmission can be reduced compared with MAC-independent opportunistic routing & encoding (MORE) [11]. Our numerical results show that the proposed scheme performs significantly better that traditional routing and opportunistic routing in which channel assignment strategy is employed.Comment: 5 pages, 4 figures, to appear in Proc. of IEEE GlobeCom 201

Sensing and detection of a primary radio signal in a cognitive radio environment using modulation identification technique

In today’s society, the need for the right information at the right time and the right place as well as increased number of high bandwidth wireless multimedia services and the explosive proliferation of smart phone and tablet devices has led to increase in demand for and use of radio spectrum, which is the primary enabler of wireless communications. With this increase, the principal engineering challenge in wireless communications domain is now on how to effectively manage the radio spectrum to ensure its sustainability for future emerging wireless devices, since virtually all usable radio frequencies for wireless communications have been licensed to commercial users and government agencies. Traditionally, the approach to radio spectrum management has been based on a fixed allocation policy, whereby licenses are issued to users or operators for the usage of frequency bands. With a license, operators have the exclusive right to use the allocated frequency bands for assigned services on a longterm basis. However, over the last ten years, this strict allocation policy has been subjected to a lot of criticism because of its observed contribution to radio spectrum scarcity and underutilization. In mitigating these negative effects of the current radio spectrum management policy, one of the suggested measures is to open up the licensed frequency bands to unlicensed users on a non-interference basis to licensed users. In this new spectrum access system, an unlicensed or secondary user can opportunistically operate in unused licensed spectrum bands without interfering with the licensed or primary user, thereby reducing radio spectrum scarcity and at the same time increasing the efficiency of the radio spectrum utilization. In achieving this objective, there is a need to develop a radio engine that can sense its environment to determine the presence of primary users. Cognitive radio is seen as the enabling technology for opportunistic spectrum sharing. It is a radio with the capability to sense and understand its environment, and proactively alter its operational mode as needed to avoid interference with a primary user. To ensure interference-free use to the primary user, spectrum sensing and detection has been observed as a key functionality of cognitive radio. However, there is currently no single sensing method that can reliably sense and detect all forms of primary radios’ signals in a cognitive radio environment. Therefore, in order to achieve this goal, this thesis addresses the problem of accurate and reliable sensing and detecting of a primary radio signal in a cognitive radio environment. The principal research issue addressed is the possibility of sensing and detecting all forms of primary radio signals in a cognitive radio environment. This objective was achieved by developing an adaptive cognitive radio engine that can automatically recognize different forms of modulation schemes in a cognitive radio environment. The thesis pictures spectrum sensing as the combination of signal detection and modulation classification, and uses the term Automatic Modulation Classification (AMC) to denote this combined process. The hypothesis behind this detection method is that, since all transmitters using the radio spectrum make use of one modulation scheme or another, the ability to automatically recognize modulation schemes is sufficient to confirm the presence of a primary user signal while the opposite confirms absence of a primary user signal. The research work methodology was divided into two stages. The first stage involves the development of an automatic modulation recognition (AMR) or AMC using an Artificial Neural Network (ANN). The second stage involves the development of the Cognitive Radio Engine (CRE), which has the developed AMR as its core component. The developed CRE was extensively evaluated to determine its performance. The overall numerical results obtained from the developed CRE’s evaluation shows that the developed CRE can reliably and accurately detect all the modulation schemes considered without bias towards a particular Signal-to-Noise Ratio (SNR) value, as well as any modulation scheme. The research work also revealed that single spectrum sensing and detection method can only be achieved when a general feature common to all radio signals is employed in its development rather than using features that are limited to certain signal types