Ahmed K. Sultan

Sensing and Transmit Energy Optimization for an Energy Harvesting Cognitive Radio

We consider a cognitive radio setting in which the secondary user is an energy harvester with a finite capacity battery. The primary user operates in a time-slotted fashion. At the beginning of each time slot, the secondary user, aiming at maximizing its throughput, may remain idle or carry out spectrum sensing to detect primary activity. The decision is determined by the secondary belief regarding primary activity and the amount of stored energy. We formulate this problem as a Markov decision process. We illustrate the optimal policy, compare it with a myopic policy, and investigate the variation of throughput with various system parameters.

Keys Through ARQ: Theory and Practice

This paper develops a novel framework for sharing secret keys using the Automatic Repeat reQuest (ARQ) protocol. We first characterize the underlying information theoretic limits, under different assumptions on the channel spatial and temporal correlation function. Our analysis reveals a novel role of “dumb antennas” in overcoming the negative impact of spatial correlation on the achievable secrecy rates. We further develop an adaptive rate allocation policy, which achieves higher secrecy rates in temporally correlated channels, and explicit constructions for ARQ secrecy coding that enjoy low implementation complexity. Building on this theoretical foundation, we propose a unified framework for ARQ-based secrecy in Wi-Fi networks. By exploiting the existing ARQ mechanism in the IEEE 802.11 standard, we develop security overlays that offer strong security guarantees at the expense of only minor modifications in the medium access layer. Our numerical results establish the achievability of nonzero secrecy rates even when the eavesdropper channel is less noisy, on the average, than the legitimate channel, while our Linux-based prototype demonstrates the efficiency of our ARQ overlays in mitigating all known, passive and active, Wi-Fi attacks at the expense of a minimal increase in the link setup time and a small loss in throughput.

Admission and Power Control for Spectrum Sharing Cognitive Radio Networks

We investigate the problem of admission and power control considering a scenario where licensed, or primary, users and cognitive radios, or secondary users, are transmitting concurrently over the same band. The primary users share a common receiver and the interference on this receiver from secondary users should be strictly limited to a certain level. Each secondary link is assumed to have a minimum quality of service (QoS) requirement that should be satisfied together with the interference limit constraint, otherwise the secondary link is not admitted. Under those constraints, admission and power control for secondary users are investigated for two main optimization objectives. First, we maximize the number of admitted secondary links. Second, we maximize the sum throughput of the admitted secondary links. The first problem is NP-hard, hence we provide a distributed close-to-optimal solution based on local measurements at each user and a limited amount of signaling. For the second problem, which is non-convex, we propose a suboptimal algorithm based on sequential geometric programming. The proposed algorithms are compared with previously related work to demonstrate their relative efficiency in terms of outage probability, complexity and achievable throughput.

QOS-Constrained Multiuser Peer-to-Peer Amplify-and-Forward Relay Beamforming

A wireless communication scenario is considered with K single-antenna source-destination pairs communicating through several half-duplex amplify-and-forward MIMO relays where each source is targeting only one destination. The relay beamforming matrices are designed in order to minimize the total power transmitted from the relays subject to quality of service constraints on the received signal to interference-plus-noise ratio at each destination node. Due to the nonconvexity of this problem, several approximations have been used in the literature to find a computationally efficient solution. A novel solution technique is developed in which the problem is decomposed into a group of second-order cone programs (SOCPs) parameterized by K phase angles; each associated with one of the constraints. An iterative algorithm is proposed to search for the phase angles and the relay beamforming matrices sequentially. However, convergence to the global optimal beamforming matrices cannot be guaranteed. Two methods for searching for the optimal values of the phase angles are proposed (from which the optimal beamforming matrices can be obtained) using grid search and bisection and the convergence of these methods to the global optimal solution of the problem is proved. Numerical simulations are presented showing the superior performance of the proposed algorithms compared to earlier suboptimal approximations at the expense of a moderate increase in the computational complexity.

Distributed Spectrum Sensing With Sequential Ordered Transmissions to a Cognitive Fusion Center

Cooperative spectrum sensing is a robust strategy that enhances the detection probability of primary licensed users. However, a large number of detectors reporting to a fusion center for a final decision causes significant delay and also presumes the availability of unreasonable communication resources at the disposal of a network searching for spectral opportunities. In this paper, we employ the idea of sequential detection to obtain a quick, yet reliable, decision regarding primary activity. Local detectors take measurements, and only a few of them transmit the log likelihood ratios (LLR) to a fusion center in descending order of LLR magnitude. The fusion center runs a sequential test with a maximum imposed on the number of sensors that can report their LLR measurements. We calculate the detection thresholds using two methods. The first achieves the same probability of error as the optimal block detector. In the second, an objective function is constructed and decision thresholds are obtained via backward induction to optimize this function. The objective function is related directly to the primary and secondary throughputs with possible privilege for primary operation. Simulation results demonstrate the enhanced performance of the approaches proposed in this paper. We also investigate the case of fading/shadowing channels between the local sensors and the fusion center, and the situation in which the sensing cost is negligible.

Optimal Random Access for a Cognitive Radio Terminal with Energy Harvesting Capability

We consider a cognitive radio scenario with an energy harvesting secondary user (SU) attempting to access a primary channel randomly. We assume multipacket reception (MPR) capability and investigate a system in which the SU may or may not exploit the primary feedback messages. The access probabilities are obtained to maximize the secondary throughput under the constraints of primary queue stability and such that the primary queueing delay is kept below a specified value in order to guarantee a certain quality of service (QoS) for the primary user (PU). We investigate the impact of the energy queue arrivals, MPR capability, and the primary queueing delay constraint on the maximum secondary throughput.

Optimization of channel sensing time and order for cognitive radios

In this paper we consider a single cognitive radio seeking a transmission opportunity by sequentially sensing a number of statistically independent primary channels. We study the joint optimization of the time spent to sense a channel, the decision threshold to determine whether the channel is free or busy, together with the order with which the channels are sensed. The sensing time and decision threshold are assumed to be the same for all channels. The design objective is to maximize the expected secondary throughput taking sensing errors into account and penalizing for collisions that may disrupt the primary transmission. Motivated by the computational complexity of the problem, we propose suboptimal solutions that significantly reduce the complexity without sacrificing accuracy. Our results reveal a fundamental trade-off between minimizing the probability of collision with the primary user via reducing the sensing errors, which favors a longer sensing time, and increasing the secondary users throughput, which favors shorter sensing time. The suboptimal approach, for plausible simulation scenarios, is found to reduce the computational complexity by more than 89%, while maintaining a near-optimal throughput within 0.28% of the optimal performance.1

ARQ-Based Secret Key Sharing

This paper develops a novel framework for sharing secret keys using existing Automatic Repeat reQuest (ARQ) protocols. Our approach exploits the multi-path nature of the wireless environment to hide the key from passive eavesdroppers. The proposed framework does not assume the availability of any prior channel state information (CSI) and exploits only the one bit ACK/NACK feedback from the legitimate receiver. Compared with earlier approaches, the main innovation lies in the distribution of key bits among multiple ARQ frames. Interestingly, this idea allows for achieving a positive secrecy rate even when the eavesdropper experiences more favorable channel conditions, on average, than the legitimate receiver. In the sequel, we characterize the information theoretic limits of the proposed schemes, develop low complexity explicit implementations, and conclude with numerical results that validate our theoretical claims.

Single-Readout High-Density Memristor Crossbar

High-density memristor-crossbar architecture is a very promising technology for future computing systems. The simplicity of the gateless-crossbar structure is both its principal advantage and the source of undesired sneak-paths of current. This parasitic current could consume an enormous amount of energy and ruin the readout process. We introduce new adaptive-threshold readout techniques that utilize the locality and hierarchy properties of the computer-memory system to address the sneak-paths problem. The proposed methods require a single memory access per pixel for an array readout. Besides, the memristive crossbar consumes an order of magnitude less power than state-of-the-art readout techniques.

Compensated Readout for High-Density MOS-Gated Memristor Crossbar Array

Leakage current is one of the main challenges facing high-density MOS-gated memristor arrays. In this study, we show that leakage current ruins the memory readout process for high-density arrays, and analyze the tradeoff between the array density and its power consumption. We propose a novel readout technique and its underlying circuitry, which is able to compensate for the transistor leakage-current effect in the high-density gated memristor array.