Joint spatial-temporal spectrum sensing and cooperative relaying for cognitive radio networks

JOINT SPATIAL-TEMPORAL SPECTRUM SENSING AND COOPERATIVE RELAYING FOR COGNITIVE RADIO NETWORKS Tuan T. Do, PhD George Mason University, Spring, 2011 Dissertation Director: Dr. Brian L. Mark The number of wireless systems and services has grown tremendously over the last two decades. As a result, the availability of wireless spectrum has become extremely limited. Cognitive radio is a new technique to overcome the issue of spectrum scarcity. In cognitive radio networks, the licensed users of the spectrum are called primary users. Secondary users equipped with cognitive radios can opportunistically transmit via so-called “spectrum holes” which can be categorized as spatial or temporal spectrum holes. In this dissertation, we propose a joint spatial-temporal spectrum sensing scheme for cognitive radios. We show that our joint spatial-temporal spectrum sensing scheme outperforms pure temporal sensing schemes. In addition, joint spatial-temporal sensing increases the point-to-point transmission capacity of cognitive radio link compared to pure temporal or spatial sensing. We also propose a temporal spectrum sensing scheme that exploits multiuser diversity in wireless networks. In wireless networks with fading, multiuser diversity exists because different users experience peak channel quality at different times. By exploiting multiuser diversity, our spectrum sensing method can outperform the spectrum sensing schemes that do not exploit multiuser diversity. We develop and analyze a joint spatial-temporal sensing scheme that incorporates cooperative relaying to further increase the capacity of a cognitive radio network. We consider both amplify-and-forward and decode-and-forward cooperative transmission strategies. Finally, we study joint spatialtemporal spectrum sensing in a multichannel cognitive radio scenario and present randomized and maximized signal-to-noise ratio algorithms that improve performance in term of symbol error probability. Chapter 1: Introduction During the past two decades, the world has witnessed a tremendous growth of the wireless communication industry with over four billion subscribers worldwide. Wireless communications have moved from first-generation (1G) systems that supported voice communication with limited roaming to third-generation (3G) systems that provide Internet connectivity and multi-media applications. The fourth-generation systems will be designed to interconnect different wireless networks such as wireless personal area networks (WPANs), wireless local area networks (WLANs) and wireless wide-area networks (WWANs). In wireless communications, all users coexisting in the same frequency band interfere with each other due to the broadcast nature of the wireless channel. As the number of wireless systems and services has grown, the availability of wireless spectrum has become severely limited as shown in the National Telecommunications and Information Administration’s (NTIA) frequency allocation chart [1]. A number of other studies, e.g., [2], [3], [4], have also shown that the wireless spectrum is highly under-utilized. This has prompted the FCC to propose opening the licensed band to unlicensed users, which has resulted in renewed interest in the concept of cognitive radios [5]. A cognitive radio (CR) transceiver is able to adapt to the dynamic environment and the network parameters to maximize the utilization of the limited radio sources while providing flexibility in wireless access. A cognitive radio must collect and process information about the licensed users within its spectrum, which requires advanced spectrum sensing and signal processing techniques. Cognitive radio enables opportunistic spectrum access which allows unlicensed users to access licensed spectrum as long as they do not cause harmful interference to the licensed users. The IEEE has formed a working group (IEEE 802.22) to develop an air interface for opportunistic spectrum access to the TV spectrum via the cognitive radio 1 technology [6]. This dissertation is motivated by potential capabilities of cognitive radios which hold tremendous promise for increasing spectral efficiency in wireless systems. 1.1 Dissertation Overview A cognitive radio can intelligently utilizes any available side information such as activity, channel conditions, codebooks or messages of licensed users. Depending on the type of available network side information and regulatory constraints, there are three main cognitive radio network paradigms: underlay, overlay, and interweave. The underlay paradigm allows cognitive users to operate if the interference caused to licensed or primary users is maintained below a given threshold. In overlay systems, cognitive radios attempt to obtain some bandwidth for their own communication without interfering with communication of primary users. In interweave systems, the cognitive radio opportunistically exploits the so-called “spectrum holes” to communicate without causing interference to primary systems. In this dissertation, we develop a framework for cognitive radio systems based on the interweave network paradigm. In this paradigm, cognitive radios seek transmission opportunities through spectrum holes which can be classified as spatial [7] or temporal [8]. We first develop a spectrum sensing technique called joint spatial-temporal spectrum sensing which detects both spatial and temporal spectrum holes. By exploiting the spatial information of primary user, the performance of temporal sensing is significantly improved relative to pure temporal sensing which does not use knowledge of primary user’s spatial information. We also propose a new spectrum sensing scheme that exploits multiuser diversity in wireless networks. Multiuser diversity is a phenomenon inherent in wireless networks provided by independent, time-varying channels across different users. In traditional cellular networks, multiuser diversity can be exploited by scheduling at any one time only the user with the best channel to transmit to the base station. Diversity gain arises from the fact that in a system with many users, whose channels vary independently, there is likely to be a user whose channel is near its peak capacity at any given time. Our multiuser diversity spectrum sensing scheme exploits the independent channel fading among secondary nodes 2 to improve the performance of spectrum sensing. Our scheme significantly outperforms other schemes that do not exploit multiuser diversity. We then propose a cooperative transmission scheme for cognitive radio networks based on spectrum holes determined through joint spatial-temporal sensing. In our scheme, a secondary transmitter communicates with a secondary receiver through relay nodes when the primary transmitter is ON and the maximum interference-free transmit power (MIFTP) is not sufficient for a direct transmission to reach the secondary receiver. When the primary transmitter is OFF, the secondary transmitter can communicate directly with the secondary receiver by transmitting at a higher power. The secondary receiver then combines the signal from the relay node and the direct signal from secondary transmitter to achieve a better signal-to-noise ratio. Our cooperative transmission scheme significantly outperforms the traditional cooperative transmission schemes that employ only spatial or temporal sensing knowledge. 1.2 Summary of chapters • In Chapter 2, we introduce the basic concepts and terminology of opportunistic spectrum access and cognitive radios. We also discuss the research literature relevant to the contributions of this dissertation. The relevant literature includes papers related to cooperative spectrum sensing, multiuser diversity and cooperative communication. • In Chapter 2.6, we propose a joint spatial-temporal sensing scheme for opportunistic spectrum sharing in cognitive radio networks. The system model consists of a primary transmitter with unknown location and transmit power, which alternates between ON and OFF states, with respect to a given frequency channel. Spatial spectrum sensing is employed to estimate the maximum interference-free transmit power for a secondary node, during an ON period. Estimates of the primary transmitter’s location and transmit power obtained in the course of spatial sensing are used by a fusion center to select a subset of the secondary nodes to make a temporal sensing decision, i.e., a