Karama Hamdi

Power Control in Cognitive Radio Systems Based on Spectrum Sensing Side Information

Cognitive radio has been recently proposed as a promising technology to improve the spectrum utilization efficiency by intelligently sensing and accessing some vacant bands of licensed users. In this paper, we consider the coexistence between a cognitive radio and a licensed user in order to enhance the spectrum efficiency. We develop an approach to allow the cognitive radio to operate in the presence of the licensed user. In order to minimize the interference to the licensed user, the transmit power of the cognitive radio is controlled by using the side information of spectrum sensing. Numerical results will show that the quality of service for the licensed user can be guaranteed in the presence of the cognitive radio by the proposed approach.

Opportunistic spectrum sharing in cognitive MIMO wireless networks

Cognitive radio has been recently proposed as a promising technology to improve the spectrum utilization. In this paper, we consider the spectrum sharing between a large number of cognitive radio users and a licensed user in order to enhance the spectrum efficiency. With the deployment of M antennas at the cognitive base station, an opportunistic spectrum sharing approach is proposed to maximize the downlink throughput of the cognitive radio system and limit the interference to the primary user. In the proposed approach, cognitive users whose channels are nearly orthogonal to the primary user channel are pre-selected so as to minimize the interference to the primary user. Then, M best cognitive users, whose channels are mutually near orthogonal to each other, are scheduled from the preselected cognitive users. A lower bound of the proposed cognitive system capacity is derived. It is then shown that opportunistic spectrum sharing approach can be extended to the multiple input/ multiple-output (MIMO) case, where a receive antenna selection is utilized in order to further reduce the computational and feedback complexity. Simulation results show that our proposed approach is able to achieve a high sum-rate throughput, with affordable complexity, when considering either single or multiple antennas at the cognitive mobile terminals.

Joint Beamforming and Scheduling in Cognitive Radio Networks

Cognitive radio has been recently proposed as a promising technology to improve the spectrum utilization. In this paper, we consider the coexistence between a large number of cognitive radio users and a licensed user in order to enhance the spectrum efficiency. With the deployment of M antennas at the cognitive base station, an efficient transmit beamforming technique combined with user selection is proposed to maximize the downlink throughput and satisfy the signal-to-interference- and-noise ratio (SINR) constraint as well as limit interference to the primary user. In the proposed user selection algorithm, cognitive users who are nearly orthogonal to the primary user are first pre-selected so as to minimize the mutual interference. Then, M best cognitive users who are nearly mutual orthogonal to each other are scheduled from those pre-selected cognitive users. Simulation results show that our proposed method is able to achieve high sum-rate throughput, with affordable complexity. Moreover, our proposed technique with equal power allocation suffers a negligible performance loss compared to the one with the optimal power allocation.

Uplink Scheduling with QoS Provisioning for Cognitive Radio Systems

Scheduling schemes have been extensively studied in the framework of cellular networks, but the emergence of new system concepts, such as cognitive radio, brings this topic into the focus of research again. In this paper, we investigate multiuser uplink scheduling with quality-of-service (QoS) provisioning for multiple cognitive users working at the same area with a primary user. In this work, the proposed scheduling schemes attempt to provide a satisfactory tradeoff between maximizing the system capacity, achieving fairness among cognitive users, minimizing the interference to the primary user, and satisfying delay constraints to individual cognitive user. Simulation results are presented to evaluate the performance of the proposed scheduling schemes.

Power, Sensing Time, and Throughput Tradeoffs in Cognitive Radio Systems: A Cross-Layer Approach

Cognitive radio has the ability to listen to the wireless channel, detect the vacant spectrum bands, and make use of them. However, the sensing ability of this smart radio may not be perfect which may induce interference to the primary system. One of the main challenges in cognitive communication lies therefore in striking a balance between the conflicting goals of minimizing the interference to the primary system and maximizing the performance of the secondary one. In this paper, we formulate a cross-layer optimization problem to design the sensing time and optimize the transmit power in order to maximize the cognitive system throughput while keeping the interference to the primary user under a threshold constraint. We study the impact of sensing time and power adaptation on the performance of the cognitive radio system. Through numerical analysis, we find that optimizing the transmit power of the cognitive user and the sensing time play an important role in maximizing the system throughput.

Impact of Noise Power Uncertainty on Cooperative Spectrum Sensing in Cognitive Radio Systems

One of the main challenges in cognitive radio (CR) communications lies in the system robustness to uncertainties. In this paper, we examine the impact of the noise power uncertainty on the performance of various detectors in CR networks. We consider both single and multiple CR nodes. For the single CR case, we compare the performance of the energy and likelihood ratio test (LRT) detectors in the presence of noise uncertainties. It is shown that both detectors perform about the same. We shall also investigate cooperative spectrum sensing based on soft-information combining, where the cooperating CR nodes experience different noise power uncertainties. We then propose a simple detection scheme that is more robust to noise variations and uncertainties than the conventional detection schemes. Numerical results are presented to verify the theory and demonstrate the robustness improvement of the proposed detection scheme.

Low-Complexity Antenna Selection and user Scheduling in Cognitive MIMO Broadcast Systems

In this paper, we consider the coexistence between a large number of cognitive radio users and a licensed user in order to enhance the spectrum efficiency. Zero-forcing beamforming (ZFB) is utilized as a downlink preceding technique that precancels inter-user interference in our multiuser cognitive multiple-input/multiple-output (MIMO) system. When there is a large number of users, the system performance can be significantly increased by selecting a subset of users and a set of receive antennas for each user. In particular, to reduce the complexity, we propose a receive antenna selection method followed by multiuser selection in order to maximize the downlink throughput as well as mitigate the interference to the primary user. Performance results show that our proposed method is able to achieve significant complexity reduction at the expense of a little sum-rate throughput loss.

Opportunistic Spectrum Sharing in Relay-Assisted Cognitive Systems With Imperfect CSI

In this paper, we consider spectrum sharing between cognitive radio (CR) users and a licensed primary user (PU) to enhance the spectrum efficiency. In the considered scenario, the PU is not able to successfully transmit data to the intended receiver. In this case, the cognitive base station (CBS) in the vicinity of the primary network offers its help to transmit the primary data. In return, the CR system shares the spectrum with the primary system. In particular, we formulate an opportunistic spectrum sharing approach that determines the optimal beamforming weights at the CBS to maximize the overall worst throughput of the CRs while guaranteeing a certain quality of service (QoS) for the PU. Various formulations of beamforming are proposed, which consider different relaying scenarios, including robust designs that are applicable with imperfect channel state information (CSI) at the PU. The original optimization problems are nonconvex and do not have any closed-form solutions. However, using a convex optimization approach, we transform them into convex forms and find approximate solutions using semidefinite programming (SDP) along with randomization techniques. We consider different examples that demonstrate the efficiency of the proposed approach.

Priority-Based Zero-Forcing in Spectrum Sharing Cognitive Systems

We consider a spectrum sharing scenario between cognitive radio (CR) users and a licensed primary user (PU), in which the PU is not able to successfully transmit data to its destined receiver. The cognitive base station (CBS) in the vicinity of the primary network, offers its help to transmit the primary data. In return, the CR system is able to share the spectrum with the primary system. We formulate an opportunistic spectrum sharing approach that determines the transmit beamforming weights in order to maximize the overall throughput of the CRs while guaranteeing the quality-of-service (QoS) of the PU. By applying algorithms based on zero-forcing beamforming (ZFB) along with optimal power allocation, the proposed approach is able to achieve cognitive and primary systems requirements.