We design distributed online learning and channel access for secondary users in a cognitive radio network. Our goal is to design channel selection and access that can effectively adapt to a wide range of traffic load patterns in the primary network. We propose a distributed adaptive learning and access policy by applying stochastic learning automata (SLA), where each secondary user (SU) probabilistically chooses one of the most available channels to access, with the channel selection probabilities being updated based on the collision events. Our design includes two underlying distributed learning algorithms: learning of primary channel availabilities from each SU's own sensing history, and SLA-based learning of channel selection from each SU's own collision history for collision avoidance. We show that some existing distributed access policies can be viewed as special cases of our proposed adaptive policy, with a set of fixed channel selection probabilities. Next, we formulate the distributed channel selection and access problem as a noncooperative game. We show that it is an exact potential game with at least one pure strategy Nash equilibrium (NE). We prove that, under our proposed adaptive policy, the channel selection probabilities converge toward a pure strategy NE of the game. Simulation demonstrates the effectiveness of our proposed adaptive policy in a wide range of distributions of mean channel availabilities, as compared with other existing policies.

We consider the design of dynamic spectrum access (DSA) mechanism. Assuming heterogeneous primary channels with distinct availability statistics unknown to each secondary user (SU), we consider the auction-based approaches for spectrum access. We first apply a unit demand (UD) auction by exploring the instantaneous link condition of each SU for its throughput maximization. To address the disadvantages faced in the UD auction, we propose a learning-based unit demand (LBUD) auction. It incorporates a distributed learning of the primary channel availabilities into the auction mechanism to explore both primary channel availability statistics and instantaneous link gains of the SUs for their throughput maximization. The new mechanism not only substantially reduces communication overhead, but also improves the SUs' throughputs when the primary channels have dissimilar availability statistics. We show that the proposed LBUD auction for channel allocation among SUs preserves the strong property of the UD auction. We further propose an adaptive price increment algorithm to improve convergence speed of the iterative procedure used in the auction. Numerical results show the effectiveness of our proposed auction mechanism in terms of the throughput gain.

We consider the design of a distributed online learning and access mechanism for dynamic spectrum access, where channel availability statistics are unknown to each secondary user (SU). Unlike existing distributed access policies, we explore the instantaneous channel gain of SUs' channels for multi-user multi-channel diversity gain. We consider an auction-based approach. For the primary channels with heterogeneous statistics, we apply the unit demand auction [1] to determine each SU's selection of a primary channel based on its instantaneous rate over each channel. We further propose a learning based unit demand (LBUD) auction, where each SU only bids for the M-best channels estimated by itself through distributed learning. The new mechanism not only reduces communication overhead, but also improves the throughput performance when the primary channels have dissimilar availability statistics. In addition, we show that the LBUD auction preserves the strong property of unit demand auction, i.e. it is dominant strategy incentive compatible. To improve the convergence speed of the iterative procedure of channel allocation in the auction, we also propose an adaptive price increment algorithm. Simulations show the effectiveness of our proposed auction mechanism in throughput gain by exploring instantaneous channel fade.

Social-aware data diffusion can improve the dissemination performance in vehicular ad hoc networks (VANETs). However, if some vehicles lie their social claims and vehicle location information is not protected, social-aware data diffusion may not work well. In this paper, to tackle the security and privacy challenges existing in social-aware data diffusion, we propose an efficient vehicle social evaluation (EVSE) scheme, which enables each vehicle to show its authentic social evaluation to others while without disclosing its past location information. As a result, it can meet the prerequisites for the success of social-aware data diffusion in VANET.

We consider a relay network which consists of two transceivers and r relay nodes. We study a half-duplex two-way relaying scheme. First, the two transceivers transmit their information symbols simultaneously and the relays receive a noisy mixture of the two transceiver signals. Then each relay adjusts the phase and the amplitude of its received signal by multiplying it with a complex beamforming coefficient and transmits the so-obtained signal. Aiming at optimally calculating the beamforming weight vector as well as the transceiver transmit powers, we minimize the total transmit power subject to two constraints on the receive signal-to-noise ratios (SNRs) at the two transceivers. We show that the optimal weight vector can be obtained through a simple iterative algorithm which enjoys a linear computational complexity per iteration.

We consider a wireless network consisting of a single-antenna transmitter, a single-antenna receiver, and a multi-antenna relay node. For such a network, we introduce the novel approach of general rank beamforming. In this approach, the relay multiplies the vector of its received signals by a general-rank complex matrix to obtain a new vector. Each entry of this new vector is then transmitted on one of the antennas available at the relay. We show that maximizing the receiver SNR subject to total relay power constraint yields a closed-form solution for the beamforming matrix. We also prove that if the channel coefficients from the transmitter to the relay antennas and those from the relay antennas to the receiver are statistically independent, the general rank beamforming approach results in a rank-one solution for the beamforming matrix.

The problem of distributed beamforming is considered for a network which consists of a transmitter, a receiver, and r relay nodes. Assuming that the second order statistics of the channel coefficients are available, we design a distributed beamforming technique via maximization of the receiver signal-to-noise ratio (SNR) subject to individual relay power constraints. We show that using semi-definite relaxation, this SNR maximization can be turned into a convex feasibility semi-definite programming problem, and therefore, it can be efficiently solved using interior point methods. We also obtain a performance bound for the semi-definite relaxation and show that the semi-definite relaxation approach provides a c-approximation to the (nonconvex) SNR maximization problem, where c = O((log r)-1) and r is the number of relays.

Universal access to broadband networks is a major principle advanced by the Canadian government to guide the development and implementation of Canada's infrastructure. Satellites are uniquely qualified to ensure that broadband services are available to all Canadians at an affordable cost. To this effect, in this paper, an advanced high-capacity Ka-band satellite, which can ubiquitously extend the reach of broadband services to areas unserved or underserved by terrestrial networks, is proposed. The satellite has a bentpipe architecture with coverage of all of Canada via small elliptical beams. The satellite can provide Canadian households, government institutions, and enterprises with low-cost, two-way, high-speed, bandwidth-on-demand access to broadband services, while using attractive user terminals, in terms of size, cost, throughput, and performance. This paper presents the baseline definition of this advanced satellite, and discusses all aspects of the system design.

An advanced satellite concept is proposed, in light of the rapid growth of DBS, the keen demand for faster communications, the shortcomings associated with terrestrial systems, and the major principle of universal access. The proposed multi-beam, high-power, high-capacity satellite-with a ubiquitous coverage of North America and attractive user terminals in terms of size, cost, and performance-can offer local and national DBS services as well as wideband interactive multimedia services.

Several non-minimum-bandwidth partial-response-signaling (PRS) techniques were compared in the above paper (ibid., vol.COM-35, p.475-80, April 1987). One of the criteria used for the comparison was the robustness to the timing jitter. The commenter shows that according to this criterion the duobinary signaling technique is superior to the dicode scheme at low values of the roll-off factor, in contradiction to the conclusion in the original study. In reply the author agrees that the comment is correct and that unnormalized and normalized figure-of-merit plots show different aspects of timing jitter sensitivity as a function of excess bandwidth.>

This paper introduces a novel class of detectors, which has a symbol-by-symbol, multisample, transversal filter-based structure. The essence of the proposed detectors is based on a noise estimationcancellation technique. By exploiting the noise correlation among the received samples, a linear minimum mean-squared estimate of the existing noise is made and subsequently cancelled. As an illustration of the detection principle, partial response signaling systems of the form1 \pm D^{m}are considered. The effects of the system bandwidth, the number of exploited samples and filtering allocation, on the system performance are thoroughly examined. It is shown that with optimum filtering allocation, the proposed detectors, while having simple structures, give substantial performance gains over conventional one-sample detectors.

In this correspondence, the effect of pulse shape on the performance of nonminimum bandwidth partial response signaling (PRS) systems is studied, using the measures of speed tolerance, eye width, and robustness to sampling phase jitter. In general, in modified duobinary(1- D^{2})and dicode(1 - D)systems, linear rolloff pulse shaping performs better than raised cosine rolloff, while the raised cosine rolloff pulse spectrum is better in the duobinary(1 + D)system.