Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks

By Rui Zhang, Ying-Chang Liang. IEEE Journal on Selected Topics in Signal Processing, 2007

881 citations recorded by the source corpus.

In cognitive radio (CR) networks, there are scenarios where the secondary (lower priority) users intend to communicate with each other by opportunistically utilizing the transmit spectrum originally allocated to the existing primary (higher priority) users. For such a scenario, a secondary user usually has to tradeoff between two conflicting goals at the same time: one is to maximize its own transmit throughput; and the other is to minimize the amount of interference it produces at each primary receiver. In this paper, we study this fundamental tradeoff from an information-theoretic perspective by characterizing the secondary user's channel capacity under both its own transmit-power constraint as well as a set of interference-power constraints each imposed at one of the primary receivers. In particular, this paper exploits multi-antennas at the secondary transmitter to effectively balance between spatial multiplexing for the secondary transmission and interference avoidance at the primary receivers. Convex optimization techniques are used to design algorithms for the optimal secondary transmit spatial spectrum that achieves the capacity of the secondary transmission. Suboptimal solutions for ease of implementation are also presented and their performances are compared with the optimal solution. Furthermore, algorithms developed for the single-channel transmission are also extended to the case of multichannel transmission whereby the secondary user is able to achieve opportunistic spectrum sharing via transmit adaptations not only in space, but in time and frequency domains as well. Simulation results show that even under stringent interference-power constraints, substantial capacity gains are achievable for the secondary transmission by employing multi-antennas at the secondary transmitter. This is true even when the number of primary receivers exceeds that of secondary transmit antennas in a CR network, where an interesting "interference diversity" effect can be exploited.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/aa4f10a97a7d02c0cdfd8ec2357205de088dd79f

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Citations in the corpus

Cooperative Interference Management With MISO Beamforming (2009, methodology): “In [14], it was proved that the solution for Problem (9) is rank-one, i.”
Optimal Resource Allocation in Coordinated Multi-Cell Systems (2013, background): “Underlay cognitive radio is a scenario where a secondary system is allowed to use the licensed spectrum of a primary system if it causes mild interference on the primary system [90, 120, 230, 327]; see Figure 1.”
Optimum Co-Design for Spectrum Sharing between Matrix Completion Based MIMO Radars and a MIMO Communication System (2015, methodology): “The channels are Rayleigh fading and are consistent with a flat fading model assumption [5]–[9], [31], [32], [44], [45].”
Dynamic Resource Allocation in Cognitive Radio Networks (2010, methodology): “ming (SOCP) [14] problem, which is convex and thus can be efﬁciently solved by available convex optimization softwares [15]. Alternatively, (P1-S) can be shown equivalent to its Lagrange dual problem [13], which is a convex semi-deﬁnite programming (SDP) [14] problem and is thus efﬁciently solvable ”
Modulation in the Air: Backscatter Communication Over Ambient OFDM Carrier (2017, background): “1 can be considered as a spectrum sharing system [4], [26].”
Optimal power allocation for fading channels in cognitive radio networks: Ergodic capacity and outage capacity (2008, background): “It is noted that optimal design of SU transmission strategy under interference-power constraints at PU receivers has a lso been studied in [11] for multi-antenna CR transmitters, and in [12] for multiple CR transmitters in a m ultiple-access channel (MAC).”
Spectrum Sharing for Device-to-Device Communication in Cellular Networks (2013, methodology): “Multi-antenna techniques are used in [17]–[19] to minimize secondary interference to primary network.”
MIMO Broadcasting for Simultaneous Wireless Information and Power Transfer (2011, methodology): “Proof: The proof is similar to that of Theorem 2 in [16], and is thus om itted for brevity.”
Fifty Years of MIMO Detection: The Road to Large-Scale MIMOs (2015, methodology): “Aiming for gleaning the benefits of both the CR and MIMO techniques, MIMO cognitive radio has also been studied from various perspectives [632]–[642].”
Optimal Resource Allocation for MIMO Ad Hoc Cognitive Radio Networks (2008, methodology): “Point-to-point MIMO links were studied in [35] under CR interference constraints, and a similar setup was considered in [34].”
Communications and Signals Design for Wireless Power Transmission (2016, background): “wireless communication systems, such as as the interferencetemperature constraints in cognitive radio systems [167], [168].”
Cognitive radio networks (2008, neutral): “Extensions to channels in which both the primary and secondary networks form classical multiple-access channels has been considered in [25], while cognitive transmissions using multiple-anten-nas, without asymmetric transmitter cooperation has been considered in [26].”
Radar and Communication Coexistence: An Overview: A Review of Recent Methods (2019, background): “A fairly natural evolution of radar and communication Support recovery is digitally performed on the low rate samples. co-existence is to use radar to perform communication, The prototype successfully recovers the support of the communication transmitted bands, as demonstrated in Fig.”
Multi-antenna based spectrum sensing for cognitive radios: A GLRT approach (2010, background): “Finally, multiantenna transceivers have also been studied in [18] for transmit beamforming instead of spectrum sensing for CRs.”
Breaking Spectrum Gridlock With Cognitive Radios: An Information Theoretic Perspective (2009, background): “Interestingly, it turns out that unit rank beamforming remains the optimal strategy at the cognitive transmitter [31].”