Constrained Bayesian Active Learning of Interference Channels in Cognitive Radio Networks

In this paper, a sequential probing method for interference constraint learning is proposed to allow a centralized Cognitive Radio Network (CRN) accessing the frequency band of a Primary User (PU) in an underlay cognitive scenario with a designed PU protection specification. The main idea is that the CRN probes the PU and subsequently eavesdrops the reverse PU link to acquire the binary ACK/NACK packet. This feedback indicates whether the probing-induced interference is harmful or not and can be used to learn the PU interference constraint. The cognitive part of this sequential probing process is the selection of the power levels of the Secondary Users (SUs) which aims to learn the PU interference constraint with a minimum number of probing attempts while setting a limit on the number of harmful probing-induced interference events or equivalently of NACK packet observations over a time window. This constrained design problem is studied within the Active Learning (AL) framework and an optimal solution is derived and implemented with a sophisticated, accurate and fast Bayesian Learning method, the Expectation Propagation (EP). The performance of this solution is also demonstrated through numerical simulations and compared with modified versions of AL techniques we developed in earlier work.Comment: 14 pages, 6 figures, submitted to IEEE JSTSP Special Issue on Machine Learning for Cognition in Radio Communications and Rada

Studies on efficient spectrum sharing in coexisting wireless networks.

Wireless communication is facing serious challenges worldwide: the severe spectrum shortage along with the explosive increase of the wireless communication demands. Moreover, different communication networks may coexist in the same geographical area. By allowing multiple communication networks cooperatively or opportunistically sharing the same frequency will potentially enhance the spectrum efficiency. This dissertation aims to investigate important spectrum sharing schemes for coexisting networks. For coexisting networks operating in interweave cognitive radio mode, most existing works focus on the secondary network’s spectrum sensing and accessing schemes. However, the primary network can be selfish and tends to use up all the frequency resource. In this dissertation, a novel optimization scheme is proposed to let primary network maximally release unnecessary frequency resource for secondary networks. The optimization problems are formulated for both uplink and downlink orthogonal frequency-division multiple access (OFDMA)-based primary networks, and near optimal algorithms are proposed as well. For coexisting networks in the underlay cognitive radio mode, this work focuses on the resource allocation in distributed secondary networks as long as the primary network’s rate constraint can be met. Global optimal multicarrier discrete distributed (MCDD) algorithm and suboptimal Gibbs sampler based Lagrangian algorithm (GSLA) are proposed to solve the problem distributively. Regarding to the dirty paper coding (DPC)-based system where multiple networks share the common transmitter, this dissertation focuses on its fundamental performance analysis from information theoretic point of view. Time division multiple access (TDMA) as an orthogonal frequency sharing scheme is also investigated for comparison purpose. Specifically, the delay sensitive quality of service (QoS) requirements are incorporated by considering effective capacity in fast fading and outage capacity in slow fading. The performance metrics in low signal to noise ratio (SNR) regime and high SNR regime are obtained in closed forms followed by the detailed performance analysis

Artificial-Noise-Aided Secure Multi-Antenna Transmission with Limited Feedback

We present an optimized secure multi-antenna transmission approach based on artificial-noise-aided beamforming, with limited feedback from a desired single-antenna receiver. To deal with beamformer quantization errors as well as unknown eavesdropper channel characteristics, our approach is aimed at maximizing throughput under dual performance constraints - a connection outage constraint on the desired communication channel and a secrecy outage constraint to guard against eavesdropping. We propose an adaptive transmission strategy that judiciously selects the wiretap coding parameters, as well as the power allocation between the artificial noise and the information signal. This optimized solution reveals several important differences with respect to solutions designed previously under the assumption of perfect feedback. We also investigate the problem of how to most efficiently utilize the feedback bits. The simulation results indicate that a good design strategy is to use approximately 20% of these bits to quantize the channel gain information, with the remainder to quantize the channel direction, and this allocation is largely insensitive to the secrecy outage constraint imposed. In addition, we find that 8 feedback bits per transmit antenna is sufficient to achieve approximately 90% of the throughput attainable with perfect feedback.Comment: to appear in IEEE Transactions on Wireless Communication

Green Communication via Power-optimized HARQ Protocols

Recently, efficient use of energy has become an essential research topic for green communication. This paper studies the effect of optimal power controllers on the performance of delay-sensitive communication setups utilizing hybrid automatic repeat request (HARQ). The results are obtained for repetition time diversity (RTD) and incremental redundancy (INR) HARQ protocols. In all cases, the optimal power allocation, minimizing the outage-limited average transmission power, is obtained under both continuous and bursting communication models. Also, we investigate the system throughput in different conditions. The results indicate that the power efficiency is increased substantially, if adaptive power allocation is utilized. For instance, assume Rayleigh-fading channel, a maximum of two (re)transmission rounds with rates $\{1,\frac{1}{2}\}$ nats-per-channel-use and an outage probability constraint ${10}^{-3}$. Then, compared to uniform power allocation, optimal power allocation in RTD reduces the average power by 9 and 11 dB in the bursting and continuous communication models, respectively. In INR, these values are obtained to be 8 and 9 dB, respectively.Comment: Accepted for publication on IEEE Transactions on Vehicular Technolog

Secure Transmission Design for Cognitive Radio Networks With Poisson Distributed Eavesdroppers

In this paper, we study physical layer security in an underlay cognitive radio (CR) network. We consider the problem of secure communication between a secondary transmitter-receiver pair in the presence of randomly distributed eavesdroppers under an interference constraint set by the primary user. For different channel knowledge assumptions at the transmitter, we design four transmission protocols to achieve the secure transmission in the CR network. We give a comprehensive performance analysis for each protocol in terms of transmission delay, security, reliability, and the overall secrecy throughput. Furthermore, we determine the optimal design parameter for each transmission protocol by solving the optimization problem of maximizing the secrecy throughput subject to both security and reliability constraints. Numerical results illustrate the performance comparison between different transmission protocols.ARC Discovery Projects Grant DP15010390