A Brief Journey through “Cognitive Wireless Communication Networks” Ekram Hossain, University of Manitoba, Winnipeg, Canada Vijay Bhargava, University of British Columbia, Vancouver, Canada Introduction Cognitive radio has emerged as a promising technology for maximizing the utili- tion of the limited radio bandwidth while accommodating the increasing amount of services and applications in wireless networks. A cognitive radio (CR) transceiver is able to adapt to the dynamic radio environment and the network parameters to maximize the utilization of the limited radio resources while providing ?exibility in wireless access. The key features of a CR transceiver are awareness of the radio en- ronment (in terms of spectrum usage, power spectral density of transmitted/received signals, wireless protocol signaling) and intelligence. This intelligence is achieved through learning for adaptive tuning of system parameters such as transmit power, carrier frequency, and modulation strategy (at the physical layer), and higher-layer protocol parameters. Development of cognitive radio technology has to deal with technical and pr- tical considerations (which are highly multidisciplinary) as well as regulatory - quirements. There is an increasing interest on this technology among the researchers in both academia and industry and the spectrum policy makers. The key enabling techniques for cognitive radio networks (also referred to as dynamic spectrum - cess networks) are wideband signal processing techniques for digital radio, advanced wireless communications methods, arti?cial intelligence and machine learning te- niques, and cognitive radio-aware adaptive wireless/mobile networking protocols.

A Brief Journey through “Cognitive Wireless Communication Networks” Ekram Hossain, University of Manitoba, Winnipeg, Canada Vijay Bhargava, University of British Columbia, Vancouver, Canada Introduction Cognitive radio has emerged as a promising technology for maximizing the utili- tion of the limited radio bandwidth while accommodating the increasing amount of services and applications in wireless networks. A cognitive radio (CR) transceiver is able to adapt to the dynamic radio environment and the network parameters to maximize the utilization of the limited radio resources while providing ?exibility in wireless access. The key features of a CR transceiver are awareness of the radio en- ronment (in terms of spectrum usage, power spectral density of transmitted/received signals, wireless protocol signaling) and intelligence. This intelligence is achieved through learning for adaptive tuning of system parameters such as transmit power, carrier frequency, and modulation strategy (at the physical layer), and higher-layer protocol parameters. Development of cognitive radio technology has to deal with technical and pr- tical considerations (which are highly multidisciplinary) as well as regulatory - quirements. There is an increasing interest on this technology among the researchers in both academia and industry and the spectrum policy makers. The key enabling techniques for cognitive radio networks (also referred to as dynamic spectrum - cess networks) are wideband signal processing techniques for digital radio, advanced wireless communications methods, arti?cial intelligence and machine learning te- niques, and cognitive radio-aware adaptive wireless/mobile networking protocols.

A Brief Journey through “Cognitive Wireless Communication Networks” Ekram Hossain, University of Manitoba, Winnipeg, Canada Vijay Bhargava, University of British Columbia, Vancouver, Canada Introduction Cognitive radio has emerged as a promising technology for maximizing the utili- tion of the limited radio bandwidth while accommodating the increasing amount of services and applications in wireless networks. A cognitive radio (CR) transceiver is able to adapt to the dynamic radio environment and the network parameters to maximize the utilization of the limited radio resources while providing ?exibility in wireless access. The key features of a CR transceiver are awareness of the radio en- ronment (in terms of spectrum usage, power spectral density of transmitted/received signals, wireless protocol signaling) and intelligence. This intelligence is achieved through learning for adaptive tuning of system parameters such as transmit power, carrier frequency, and modulation strategy (at the physical layer), and higher-layer protocol parameters. Development of cognitive radio technology has to deal with technical and pr- tical considerations (which are highly multidisciplinary) as well as regulatory - quirements. There is an increasing interest on this technology among the researchers in both academia and industry and the spectrum policy makers. The key enabling techniques for cognitive radio networks (also referred to as dynamic spectrum - cess networks) are wideband signal processing techniques for digital radio, advanced wireless communications methods, arti?cial intelligence and machine learning te- niques, and cognitive radio-aware adaptive wireless/mobile networking protocols.