Q. Zhao, L. Tong, A. Swami, and Y. Chen, “Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework,” IEEE Journal on Selected Areas in Communications, vol. 25, no. 3, pp. 589-600, April 2007.
A pioneering work on decentralized cognitive MAC design – provides a decision-theoretic approach which integrates the design of spectrum access with spectrum sensing at the physical layer and traffic statistics determined by the application layer of the primary network – considers a single-user scenario.
A. Ghasemi and E. S. Sousa, “Fundamental limits of spectrum-sharing in fading environments,” IEEE Transactions on Wireless Communications, vol. 6, no. 2, pp. 649-658, February 2007.
This is the pioneering work on spectrum sharing that evaluates the secondary channel capacities under the average and peak interference power constraints at the primary receiver in different fading environments. It is shown that with the same interference power limit, channel capacity in fading environments exceeds that of the AWGN channel. Impacts of correlated fading and multiple primary receivers on the channel capacity are also studied. Asymptotic capacities under different fading distributions are derived.
H. Kim and K. G. Shin, “Efficient discovery of Spectrum opportunities with MAC-layer sensing in cognitive radio networks,” IEEE Transactions on Mobile Computing, vol. 7, no. 5, pp. 533-545, May 2008.
This is one of the early papers, which studies the problem of maximizing the discovery of spectrum opportunities with MAC-layer sensing by adapting sensing periods assuming an ON/OFF alternating channel activity pattern for primary users. The parameters for the probability distributions of ON/OFF periods are estimated by using Maximum Likelihood (ML) estimators.
R. Zhang and Y.-C. Liang, “Exploiting multi-antennas for opportunistic spectrum sharing in cognitive radio networks,” IEEE Journal of Selected Topics in Signal Processing, vol. 2, no. 1, pp. 88-102, February 2008.
One of the very few works on spectrum sharing in multiple-input and multiple-output (MIMO)-based cognitive radio systems – proposes convex optimization-based methods to maximize the cognitive radio’s transmission rate under the transmit power constraint and a set of interference power constraints for any arbitrary number of primary and secondary, transmit and receive, antennas.
J. Jia, Q. Zhang, and X. Shen, “HC-MAC: A hardware-constrained cognitive MAC for efficient spectrum management,” IEEE Journal on Selected Areas in Communications, vol. 26, no. 1, pp. 106-117, January 2008.
This paper presents a hardware-constrained multichannel cognitive MAC protocol under spectrum overlay. Although it considers a single-user scenario and an independent channel usage model, this is an important contribution towards practical MAC design for cognitive radio networks.
Y. Xing, C. N. Mathur, M. A. Haleem, R. Chandramouli, and K. P. Subbalakshmi, “Dynamic spectrum access with QoS and interference temperature constraints,” IEEE Transactions on Mobile Computing, vol. 6, no. 4, pp. 423-433, April 2007.
This is a premier work on modeling and optimization of the spectrum sharing problem in a cognitive radio network considering the interference temperature constraint for primary users and the quality-of-service (QoS) requirements for secondary users. A social-optimization formulation and a game-theoretic formulation are considered, respectively, for centralized and distributed implementation of spectrum sharing.
Y. Xing, R. Chandramouli, S. Mangold, and S. Sankar N, “Dynamic spectrum access in open spectrum wireless networks,” IEEE Journal on Selected Areas in Communications, vol. 24, no. 3, pp. 626-637, March 2006.
This is one of the early works on MAC design for spectrum sharing. This paper presents a learning-based MAC protocol for spectrum-sharing wireless networks such that weighted time-fairness can be achieved among the different networks sharing the spectrum.
X. Kang, Y.-C. Liang, A. Nallanathan, H. K. Garg, and R. Zhang, “Optimal power allocation for fading channels in cognitive radio networks: Ergodic capacity and outage capacity,” IEEE Transactions on Wireless Communications, vol. 8, no. 2, pp. 940-950, February 2009.
A significant work on capacity analysis of a cognitive radio systemunder different power allocation strategies at the cognitive radios such that the interference power experienced by the primary receiver is limited - considers various combination of peak/average transmit and interference power constraints and studies the power allocation strategies to achieve the ergodic, delay-limited, and outage capacities for different fading channel models such as Rayleigh, Nakagami, and log-normal shadowing.
Y. Chen, Q. Zhao, and A. Swami, “Joint design and separation principle for opportunistic spectrum access in the presence of sensing errors,” IEEE Transactions on Information Theory, vol. 54, no. 5, pp. 2053-2071, May 2008.
A premier work on cross-layer (PHY-MAC) design - demonstrates how sensing errors at the PHY layer affects MAC design and how incorporating MAC layer information into physical layer leads to a cognitive spectrum sensor whose performance improves over time by learning from accumulating observations.
L. Zhang, Y.-C. Liang, and Y. Xin, “Joint beamforming and power allocation for multiple access channels in cognitive radio networks,” IEEE Journal on Selected Areas in Communications, vol. 26, no.1, pp. 38-51, January 2008.
A premier work on single-input multiple-output multiple access channel (SIMO-MAC) for cognitive spectrum sharing where multiple single-antenna secondary users communicate simultaneously to a multi-antenna secondary base station in the presence of multiple single-antenna primary receivers - provides insightful results on the joint beamforming and power allocation design under the transmit power constraint at each secondary transmitter and the interference power constraint at each primary receiver for two distinct objectives: sum-rate maximization and SINR balancing.
G. Bansal, M. J. Hossain, and V. K. Bhargava, “Optimal and suboptimal power allocation schemes for OFDM-based cognitive radio systems,” IEEE Transactions on Wireless Communications, 7(11): 4710-4718, November 2008.
One premier work on OFDM-based cognitive radio system which investigates the optimal power loading problem to maximize the transmission data rate while maintaining the interference caused to the primary users within a given limit.
L. B. Le and E. Hossain, “Resource allocation for spectrum underlay in cognitive wireless networks," IEEE Transactions on Wireless Communications, vol. 7, no. 12, pp. 5306-5315, December 2008.
This is one of the early papers on rate, power and admission control for cognitive radios using code-division multiple access (CDMA) in spectrum underlay scenarios – considers fairness among cognitive radios.
H. Jiang, L. Lai, R. Fan, and H. V. Poor, “Optimal selection of channel sensing order in cognitive radio,” IEEE Transactions on Wireless Communications, vol. 8, no. 1, pp. 297-303, January 2009.
Another important work on multichannel cognitive MAC protocol in a single-user scenario - provides a dynamic programming-based solution for optimal channel sensing order for a given number of time slots in the MAC layer considering adaptive modulation at the physical layer. Both the independent and correlated channel occupancy models are considered.
L. Lai, H. El Gamal, H. Jiang and H. Vincent Poor, “Cognitive Medium Access: Exploration, Exploitation and Competition,” IEEE Transactions on Mobile Computing, vol. 10, no. 2, pp. 239-253, February 2011.
This paper particularly develops the cognitive medium access with the capability of cognitive radio user to explore, exploit, and compete for the radio resource. The game theory is used to analyze the strategies of cognitive radio users to maximize the total throughput. Also, low complexity protocol is introduced based on the theoretical results
D. I. Kim, L. B. Le, and E. Hossain, "Joint rate and power allocation for cognitive radios in dynamic spectrum access environment," IEEE Transactions on Wireless Communications, vol. 7, no. 12 - part 2, pp. 5517-5527, December 2008
A significant work on joint rate, power and admission control for cognitive radios in spectrum underlay scenarios – considers a realistic scenario where power allocations for the secondary transmitters are performed based on the average (rather than instantaneous) channel gain estimates while satisfying the target interference constraint violation probability for primary receivers.
R. Zhang, Y.-C. Liang and S. Cui, “Dynamic resource allocation in cognitive radio networks,” IEEE Signal Processing Magazine, vol. 27, no. 3, pp. 102-114, May 2010.
L. Zhang, Y.-C. Liang, Y. Xin, and H. V. Poor, “Robust cognitive beamforming with partial channel state information,” IEEE Transactions on Wireless Communications, vol. 8, no. 8, pp. 4143-4153, August 2009.
An important survey on dynamic resource allocation schemes for cognitive radio systems with the interference temperature based spectrum-sharing model. Many new and challenging problems regarding the design of CR systems are formulated and some of the corresponding solutions are shown to be obtainable by restructuring some classic results known for traditional (non-CR) wireless networks.
This is the first paper addressing a robust beamforming design problem for cognitive radios.
Z. Hasan, G. Bansal, E. Hossain, and V. K. Bhargava, “Energy-efficient power allocation in OFDM- based cognitive radio systems: A risk-return model,” IEEE Transactions on Wireless Communications, 8(12): 6078-6088, December 2009.
A premier work on energy-efficient power allocation to maximize the expected transmission rate for OFDM-based cognitive radio systems – takes into account the reliability of the available sub-bands (which depends on sensing error and primary user activity), sub-band power constraints, and total allowed interference limit to the adjacent primary user bands.
M. G. Khoshkholgh, K. Navaie, and H. Yanikomeroglu, “Access strategies for spectrum sharing in fading environment: Overlay, underlay and mixed,” IEEE Transactions on Mobile Computing, vol. 9, no. 12, pp. 1780-1793, December 2010.
This is another pioneering work on the analysis of the ergodic capacity of secondary user system for different spectrum sharing strategies (underlay, overlay, and a hybrid strategy) with one primary user and one secondary user. The analysis reveals that the maximum capacity in a spectrum underlay system can be achieved with reduced signaling complexity where the channel state information between the secondary transmitter and the primary receiver may not be required for power allocation.