Mathew Sherman

Bio: Mathew Sherman is an academic researcher from BAE Systems. The author has contributed to research in topics: Communications system & Cognitive radio. The author has an hindex of 5, co-authored 6 publications receiving 355 citations.

IEEE Standards Supporting Cognitive Radio and Networks, Dynamic Spectrum Access, and Coexistence

Abstract: Cognitive radio techniques are being applied to many different communications systems. They hold promise for increasing utilization of radio frequencies that are underutilized today, allowing for improved commercial data services, and allowing for new emergency and military communications services. For example, these techniques are being considered by the U.S. FCC for communications services in unlicensed VHF and UHF TV bands. Although traditionally these techniques are closely associated with software-defined radios, many standards such as WiFi (IEEE 802.11), Zigbee (IEEE 802.15.4), and WiMAX (IEEE 802.16) already include some degree of CR technology today. Further advances are occurring rapidly. IEEE 802.22 will be the first cognitive radio-based international standard with tangible frequency bands for its operation. Standardization is at the core of the current and future success of cognitive radio. Industry stakeholders are participating in international standards activities governing the use of cognitive radio techniques for dynamic spectrum access and coexistence, next-generation radio and spectrum management, and interoperability in infrastructure-less wireless networks. This article provides a review of standardization activities for cognitive radio technologies and comments on prospects and issues for future standardization.

Recent advances in cognitive communications

Abstract: This article describes recent advances in cognitive communications. We combine the concepts of signal processing, communications, pattern classification, and machine learning to make dynamic use of the spectrum, such that the emanated signals do not interfere with the existing ones. Unlike other programs such as neXt Generation communications of the Defense Advanced Research Projects Agency, where radio scene analysis is performed to find the spectrum holes or the white space, we make use of the white, as well as the gray space for non- interfering signal transmission. We examine the possibility of employing machine perception and autonomous machine learning technologies to the autonomous design and analysis of air interfaces. The underlying premise is that a learning module will facilitate adaptation in the standard classification process so that the presence of new types of waveforms can be detected, features that best facilitate classification of the previously and newly identified signals can be determined, and waveforms can be generated by using the basis-set orthogonal to the ones present in the environment. Incremental learning and prediction allows knowledge enhancement as more snapshots of data are processed, resulting in improved decisions. Some of the contributions of this project include technological advances in signal detection, feature identification, signal classification, sub-space tracking, adaptive waveform design, machine learning, and prediction.

Survey of IEEE standards supporting cognitive radio and dynamic spectrum access

Abstract: Standardization is key to the success of many technologies. Cognitive radio (CR) is no exception. CR techniques are being applied in many different communications systems. They promise to improve the utilization of radio frequencies making room for new and additional commercial data, emergency, and military communications services [1, 2]. In the United States (US) these techniques are being considered by the Federal Communications Commission (FCC) for communications services in unlicensed VHF and UHF TV bands. Similar consideration is being given elsewhere in the world such as with Office of Communications (Ofcom) in the United Kingdom. Standardization is at the core of cognitive radiopsilas current and future successes. Industry stake-holders are participating in international standards activities governing the use of cognitive radio techniques. This article provides a survey of cognitive radio standardization activities, their past and present, and discusses prospects and issues for future standardization.

MUD Enabled Media Access Control for High Capacity, Low-Latency Spread Spectrum Communications

Abstract: Unlike conventional wireless communication systems that operate under an interference avoidance paradigm, the DARPA Interference Division Multiple Access (IDMA) program exploits multi-access interference to enable high-capacity, low-latency spread spectrum communication that requires no infrastructure or coordination. The enabling technology behind IDMA is Multi-User Detection (MUD) at the Physical Layer, which enables a receiver to simultaneously demodulate multiple interfering users. To fully exploit this new Physical Layer capability, novel Media Access Control (MAC) protocols are required that control and encourage users to collide rather than avoid interference all together. This paper discusses the motivating factors behind the IDMA MAC design and highlights the technical challenges in developing a MAC that both facilitates and exploits MUD at the Physical Layer. Particular attention is given to key decentralized MAC mechanisms, including distributed synchronization and scheduling. Analysis is presented highlighting the performance gains of IDMA over conventional adhoc communication systems, such as 802.11. Looking to the future, insight is provided into military applications and concepts of operations where IDMA technology is expected to dramatically improve performance and provide novel capabilities to the warfighter.

Interference multiple access wireless network demonstration enabled by real-time multiuser detection

Abstract: In recent outdoor, over-the-air tests and simulations, DARPA demonstrated greater than 3X improvement in aggregate wireless network throughput and latency compared to the 802.11b wireless local area network. This achievement is based on allowing multiple users to simultaneously use the same channel (time, frequency, code, etc.) without requiring a centralized infrastructure for coordination and spectrum preplanning. DARPA has developed new multi-user detection (MUD) algorithms that make it possible to exploit multi-access interference to increase network capacity. A key program goal is to apply these algorithms to next-generation warfighter communications systems for substantial capacity, latency and scalability improvements.

Cooperative Communications for Cognitive Radio Networks

Abstract: Cognitive radio is an exciting emerging technology that has the potential of dealing with the stringent requirement and scarcity of the radio spectrum. Such revolutionary and transforming technology represents a paradigm shift in the design of wireless systems, as it will allow the agile and efficient utilization of the radio spectrum by offering distributed terminals or radio cells the ability of radio sensing, self-adaptation, and dynamic spectrum sharing. Cooperative communications and networking is another new communication technology paradigm that allows distributed terminals in a wireless network to collaborate through some distributed transmission or signal processing so as to realize a new form of space diversity to combat the detrimental effects of fading channels. In this paper, we consider the application of these technologies to spectrum sensing and spectrum sharing. One of the most important challenges for cognitive radio systems is to identify the presence of primary (licensed) users over a wide range of spectrum at a particular time and specific geographic location. We consider the use of cooperative spectrum sensing in cognitive radio systems to enhance the reliability of detecting primary users. We shall describe spectrum sensing for cognitive radios and propose robust cooperative spectrum sensing techniques for a practical framework employing cognitive radios. We also investigate cooperative communications for spectrum sharing in a cognitive wireless relay network. To exploit the maximum spectrum opportunities, we present a cognitive space-time-frequency coding technique that can opportunistically adjust its coding structure by adapting itself to the dynamic spectrum environment.

A Survey on Machine-Learning Techniques in Cognitive Radios

Abstract: In this survey paper, we characterize the learning problem in cognitive radios (CRs) and state the importance of artificial intelligence in achieving real cognitive communications systems. We review various learning problems that have been studied in the context of CRs classifying them under two main categories: Decision-making and feature classification. Decision-making is responsible for determining policies and decision rules for CRs while feature classification permits identifying and classifying different observation models. The learning algorithms encountered are categorized as either supervised or unsupervised algorithms. We describe in detail several challenging learning issues that arise in cognitive radio networks (CRNs), in particular in non-Markovian environments and decentralized networks, and present possible solution methods to address them. We discuss similarities and differences among the presented algorithms and identify the conditions under which each of the techniques may be applied.

Cognitive Radio for Smart Grids: Survey of Architectures, Spectrum Sensing Mechanisms, and Networking Protocols

Abstract: Traditional power grids are currently being transformed into smart grids (SGs). SGs feature multi-way communication among energy generation, transmission, distribution, and usage facilities. The reliable, efficient, and intelligent management of complex power systems requires integration of high-speed, reliable, and secure data information and communication technology into the SGs to monitor and regulate power generation and usage. Despite several challenges, such as trade-offs between wireless coverage and capacity as well as limited spectral resources in SGs, wireless communication is a promising SG communications technology. Cognitive radio networks (CRNs) in particular are highly promising for providing timely SG wireless communications by utilizing all available spectrum resources. We provide in this paper a comprehensive survey on the CRN communication paradigm in SGs, including the system architecture, communication network compositions, applications, and CR-based communication technologies. We highlight potential applications of CR-based SG systems. We survey CR-based spectrum sensing approaches with their major classifications. We also provide a survey on CR-based routing and MAC protocols, and describe interference mitigation schemes. We furthermore present open issues and research challenges faced by CR-based SG networks along with future directions.

Supervised machine learning techniques in cognitive radio networks during cooperative spectrum handovers

Abstract: Cognitive communication model perform the investigation and surveillance of spectrum in cognitive radio networks abetment in advertent primary users (PUs) and in turn help in allocation of transmission space for secondary users (SUs). In effective performance of regulation of wireless channel handover strategy in cognitive computing systems, new computing models are desired in operating set of tasks to process business model, and interact naturally with humans or machine rather being programmed. Cognitive wireless network are trained via artificial intelligence (AI) and machine learning (ML) algorithms for dynamic processing of spectrum handovers. They assist human experts in making enhanced decisions by penetrating into the complexity of the handovers. This paper focuses on learning and reasoning features of cognitive radio (CR) by analyzing primary user (PU) and secondary user (SU) data communication using home location register (HLR) and visitor location register (VLR) database respectively. The SpecPSO is proposed for optimizing handovers using supervised machine learning technique for performing dynamic handover by adapting to the environment and make smart decisions compared to the traditional cooperative spectrum sensing (CSS) techniques.

IEEE Standards Supporting Cognitive Radio and Networks, Dynamic Spectrum Access, and Coexistence

Abstract: Cognitive radio techniques are being applied to many different communications systems. They hold promise for increasing utilization of radio frequencies that are underutilized today, allowing for improved commercial data services, and allowing for new emergency and military communications services. For example, these techniques are being considered by the U.S. FCC for communications services in unlicensed VHF and UHF TV bands. Although traditionally these techniques are closely associated with software-defined radios, many standards such as WiFi (IEEE 802.11), Zigbee (IEEE 802.15.4), and WiMAX (IEEE 802.16) already include some degree of CR technology today. Further advances are occurring rapidly. IEEE 802.22 will be the first cognitive radio-based international standard with tangible frequency bands for its operation. Standardization is at the core of the current and future success of cognitive radio. Industry stakeholders are participating in international standards activities governing the use of cognitive radio techniques for dynamic spectrum access and coexistence, next-generation radio and spectrum management, and interoperability in infrastructure-less wireless networks. This article provides a review of standardization activities for cognitive radio technologies and comments on prospects and issues for future standardization.