On performance analysis of cognitive radios

fi=vertaisarvioitu|en=peerReviewed

Cognitive Radio Systems: Performance Analysis and Optimal Resource Allocation

Rapid growth in the use of wireless services coupled with inefficient utilization of scarce spectrum resources has led to the analysis and development of cognitive radio systems. Cognitive radio systems provide dynamic and more efficient utilization of the available spectrum by allowing unlicensed users (i.e., cognitive or secondary users) to access the frequency bands allocated to the licensed users (i.e., primary users) without causing harmful interference to the primary user transmissions. The central goal of this thesis is to conduct a performance analysis and obtain throughput- and energy-efficient optimal resource allocation strategies for cognitive radio systems. Cognitive radio systems, which employ spectrum sensing mechanisms to learn the channel occupancy by primary users, generally operate under sensing uncertainty arising due to false alarms and miss-detections. This thesis analyzes the performance of cognitive radio systems in a practical setting with imperfect spectrum sensing. In the first part of the thesis, optimal power adaptation schemes that maximize the achievable rates of cognitive users with arbitrary input distributions in underlay cognitive radio systems subject to transmit and interference power constraints are studied. Simpler approximations of optimal power control policies in the low-power regime are determined. Low-complexity optimal power control algorithms are proposed. Next, energy efficiency is considered as the performance metric and power allocation strategies that maximize the energy efficiency of cognitive users in the presence of time-slotted primary users are identified. The impact of different levels of channel knowledge regarding the transmission link between the secondary transmitter and secondary receiver, and the interference link between the secondary transmitter and primary receiver on the optimal power allocation is addressed. In practice, the primary user may change its status during the transmission phase of the secondary users. In such cases, the assumption of time-slotted primary user transmission no longer holds. With this motivation, the spectral and energy efficiency in cognitive radio systems with unslotted primary users are analyzed and the optimal frame duration and energy-efficient optimal power control schemes subject to a collision constraint are jointly determined. The second line of research in this thesis focuses on symbol error rate performance of cognitive radio transmissions in the presence of imperfect sensing decisions. General formulations for the optimal decision rule and error probabilities for arbitrary modulation schemes are provided. The optimal decision rule for rectangular quadrature amplitude modulation (QAM) is characterized, and closed-form expressions for the average symbol error probability attained with the optimal detector under both transmit power and interference constraints are derived. Furthermore, throughput of cognitive radio systems for both fixed-rate and variable-rate transmissions in the finite-blocklength regime is studied. The maximum constant arrival rates that the cognitive radio channel can support with finite blocklength codes while satisfying statistical quality of service (QoS) constraints imposed as limitations on the buffer violation probability are characterized. In the final part of the thesis, performance analysis in the presence of QoS requirements is extended to general wireless systems, and energy efficiency and throughput optimization with arbitrary input signaling are studied when statistical QoS constraints are imposed as limitations on the buffer violation probability. Effective capacity is chosen as the performance metric to characterize the maximum throughput subject to such buffer constraints by capturing the asymptotic decay-rate of buffer occupancy. Initially, constant-rate source is considered and subsequently random arrivals are taken into account

Performance Analysis of Cognitive Radio Systems with Imperfect Channel Knowledge

An analytical framework is established to characterize the effects such as time allocation and variation, arising due to the incorporation of imperfect channel knowledge, that are detrimental to the performance of the cognitive radio systems. In order to facilitate hardware deployment of a cognitive radio system, received power-based estimation, a novel channel estimation technique is employed for the channels existing between the primary and the secondary systems, thus fulfilling low-complexity and versatility requirements

Joint Spatial and Spectrum Cooperation in Wireless Network.

PhDThe sky-rocketing growth of multimedia infotainment applications and broadband-hungry mobile devices exacerbate the stringent demand for ultra high data rate and more spectrum resources. Along with it, the unbalanced temporal and geographical variations of spectrum usage further inspires those spectral-efficient networks, namely, cognitive radio and heterogeneous cellular networks (HCNs). This thesis focuses on the system design and performance enhancement of cognitive radio (CR) and HCNs. Three different aspects of performance improvement are considered, including link reliability of cognitive radio networks (CNs), security enhancement of CNs, and energy efficiency improvement of CNs and HCNs. First, generalized selection combining (GSC) is proposed as an effective receiver design for interference reduction and reliability improvement of CNs with outdated CSI. A uni- ed way for deriving the distribution of received signal-to-noise ratio (SNR) is developed in underlay spectrum sharing networks subject to interference from the primary trans- mitter (PU-Tx) to the secondary receiver (SU-Rx), maximum transmit power constraint at the secondary transmitter (SU-Tx), and peak interference power constraint at the PU receiver (PU-Rx), is developed. Second, transmit antenna selection with receive generalized selection combining (TAS/GSC) in multi-antenna relay-aided communica- tion is introduced in CNs under Rayleigh fading and Nakagami-m fading. Based on newly derived complex statistical properties of channel power gain of TAS/GSC, exact ergodic capacity and high SNR ergodic capacity are derived over Nakagami-m fading. Third, beamforming and arti cial noise generation (BF&AN) is introduced as a robust scheme to enhance the secure transmission of large-scale spectrum sharing networks with multiple randomly located eavesdroppers (Eves) modeled as homogeneous Poisson Point Process (PPP). Stochastic geometry is applied to model and analyze the impact of i BF&AN on this complex network. Optimal power allocation factor for BF&AN which maximizes the average secrecy rate is further studied under the outage probability con- straint of primary network. Fourth, a new wireless energy harvesting protocol is proposed for underlay cognitive relay networks with the energy-constrained SU-Txs. Exact and asymptotic outage probability, delay-sensitive throughput, and delay-tolerant through- put are derived to explore the tradeoff between the energy harvested from the PU-Txs and the interference caused by the PU-Txs. Fifth, a harvest-then-transmit protocol is proposed in K-tier HCNs with randomly located multiple-antenna base stations (BSs) and single antenna mobile terminals (MTs) modeled as homogeneous PPP. The average received power at MT, the uplink (UL) outage probability, and the UL average ergodic rate are derived to demonstrate the intrinsic relationship between the energy harvested from BSs in the downlink (DL) and the MT performance in the UL. Throughout the thesis, it is shown that link reliability, secrecy performance, and energy efficiency of CNs and HCNs can be signi cantly leveraged by taking advantage of multiple antennas, relays, and wireless energy harvesting

Reliable and Efficient Cognitive Radio Communications Using Directional Antennas

Cognitive Radio (CR) is a promising solution that enhances spectrum utilization by allowing an unlicensed or Secondary User (SU) to access licensed bands in a such way that its imposed interference on a license holder Primary User (PU) is limited, and hence fills the spectrum holes in time and/or frequency domains. Resource allocation, which involves scheduling of available time and transmit power, represents a crucial problem for the performance evaluation of CR systems. In this dissertation, we study the spectral efficiency maximization problem in an opportunistic CR system. Specifically, in the first part of the dissertation, we consider an opportunistic CR system where the SU transmitter (SUtx) is equipped to a Reconfigurable Antenna (RA). RA, with the capabilities of dynamically modifying their characteristics can improve the spectral efficiency, via beam steering and utilizing the spectrum white spaces in spatial (angular) domain. In our opportunistic CR system, SUtx relies on the beam steering capability of RA to detect the direction of PU\u27s activity and also to select the strongest beam for data transmission to SU receiver (SUrx). We study the combined effects of spectrum sensing error and channel training error as well as the beam detection error and beam selection error on the achievable rates of an opportunistic CR system with a RA at SUtx. We also find the best duration for spectrum sensing and channel training as well as the best transmit power at SUtx such that the throughput of our CR system is maximized subject to the Average Transmit Power Constraint (ATPC) and Average Interference Constraint (AIC). In the second part of the dissertation, we consider an opportunistic Energy Harvesting (EH)-enabled CR network, consisting of multiple SUs and an Access Point (AP), that can access a wideband spectrum licensed to a primary network. Assuming that each SU is equipped with a finite size rechargeable battery, we study how the achievable sum-rate of SUs is impacted by the combined effects of spectrum sensing error and imperfect Channel State Information (CSI) of SUs–AP links. We also design an energy management strategy that maximizes the achievable sum-rate of SUs, subject to a constraint on the average interference that SUs can impose on the PU