This paper studies the temporal characteristics of the intelligent reflecting surface (IRS)-based visible light communication (VLC) channel using radiometric concepts. Throughout this study, we account for the delays experienced by the transmitted power along the continuum of paths originating at the source, passing through the IRS, reaching the detector. Then, we derive the impulse response of multi-element phase-tunable metasurface and orientation-tunable mirror array-based reflector setups for a general setting of source, reflector, and detector dimensions and relative positions. In addition, we derive simpler expressions for the two special cases, namely, the point source and the large-source small-reflector. Moreover, we present the exact expression for the delay spread and derive lower, upper bounds and asymptotic expressions when the number of reflecting elements increases for both reflector types. Finally, we study the impact of several system parameters on the temporal characterization of the two IRS-based VLC systems.

Stochastic geometry (SG) has been widely accepted as a fundamental tool for modeling and analyzing cellular networks. However, the fading models used with SG analysis are mainly confined to the simplistic Rayleigh fading, which is extended to the Nakagami-m fading in some special cases. However, neither the Rayleigh nor the Nakagami-m accounts for dominant specular components (DSCs) which may appear in realistic fading channels. In this paper, we present a tractable model for cellular networks with generalized two-ray (GTR) fading channel. The GTR fading explicitly accounts for two DSCs in addition to the diffuse components and offers high flexibility to capture diverse fading channels that appear in realistic outdoor/indoor wireless communication scenarios. It also encompasses the famous Rayleigh and Rician fading as special cases. To this end, the prominent effect of DSCs is highlighted in terms of average spectral efficiency.

Due to the massive data traffic in wireless networks, energy consumption has become a crucial concern, especially with the limited power supply of the mobile terminals and the increasing $CO_2$ emission of the cellular industry. In this context, we study the energy efficiency (EE) of MIMO spectrum sharing cognitive radio (CR) systems under power and interference constraints. We present an energy-efficient power allocation framework based on maximizing the average EE per parallel channel resulting from the singular value decomposition (SVD) eigenmode transmission. We also present a sub-optimal low-complexity power allocation scheme based on the water-filling power allocation. In the numerical results, we show that the sub-optimal power allocation achieves at least $95\%$ of the optimal performance. In addition, we show that adopting more antennas is more energy efficient for a given power budget. Finally, we show that the interference threshold has a significant effect on both the EE and the spectral efficiency at high-power regime.

In this paper, we consider a multiuser multiple-input multiple-output (MIMO) decode-and-forward (DF) relay broadcasting channel (BC) with single source, multiple energy harvesting (EH) relays, and multiple destinations. All the nodes are equipped with multiple antennas. The EH and information decoding tasks at the relays and destinations are separated over the time, which is termed as the time switching scheme. As optimal solutions for the sum-rate maximization problems of BC channels and the MIMO interference channels are hard to obtain, the end-to-end sum rate maximization problem of a multiuser MIMO DF relay BC channel is even harder. In this paper, we propose to tackle a simplified problem, where we employ the block diagonalization (BD) procedure at the source, and we mitigate the interference between the relay-destination channels using an algorithm similar to the BD method. In order to show the relevance of our low complex proposed solution, we compare it with the minimum mean-square error (mmse) solution that was shown in the literature to be equivalent to the solution of the sum-rate maximization in the MIMO broadcasting interfering channels. We also investigate the time division multiple access (TDMA) solution, which separates all the information transmissions from the source to the relays and from the relays to the destinations over time. We provide the numerical results to show the relevance of our proposed solution, in comparison with the no co-channel interference case, the TDMA-based solution, and the mmse-based solution.

In this paper, we investigate the simultaneous wireless information and power transfer in a multiple-input multiple-output decode-and-forward relay system, where the relay is an energy harvesting (EH) multi-antenna node equipped with an EH receiver and an information decoding (ID) receiver. The relay harvests the energy from the radio frequency signals sent by the source and uses it to forward the signals to the destination. The main objective in this paper is to maximize the achievable transmission rate of the overall link by optimizing the source/relay precoders. First, we study an upper bound on the maximum achievable rate where we assume that the EH and ID receivers operate simultaneously and have access to the whole power of the received signals. Afterward, we study two practical schemes, which are the power splitting and time switching schemes, where the ID and EH receivers have partial access to the power or duration of the received signals. For each scheme, we have studied the complexity and the performance comparison. In addition, we considered the case of the imperfect channel estimation error and we have observed its impact on the achievable end-to-end rate and the harvested energy at the relay.

In this work, we consider a two-hop cooperative setting where a source communicates with a destination through an intermediate relay node with a buffer. Unlike the existing body of work on buffer-aided half-duplex relaying, we consider a hybrid half-/full-duplex relaying scenario with loopback interference in the full-duplex mode. Depending on the channel outage and buffer states that are assumed available at the transmitters, the source and relay may either transmit simultaneously or revert to orthogonal transmission. Specifically, a joint source/relay scheduling and relaying mode selection mechanism is proposed to maximize the end-to-end throughput. The throughput maximization problem is converted to a linear program where the exact global optimal solution is efficiently obtained via standard convex/linear numerical optimization tools. Finally, the theoretical findings are corroborated with event-based simulations to provide the necessary performance validation.

In this paper, we investigate the simultaneous wireless information and power transfer (SWIPT) for a decode-and-forward (DF) multiple-input multiple-output (MIMO) relay system where the relay is an energy harvesting node. We consider the ideal scenario where both the energy harvesting (EH) receiver and information decoding (ID) receiver at the relay have access to the whole received signal and its energy. The relay harvests the energy while receiving the signal from the source and uses the harvested power to forward the signal to the destination. We obtain the optimal precoders at the source and the relay to maximize the achievable throughput rate of the overall link. In the numerical results, the effect of the transmit power at the source and the position of the relay between the source and the destination on the maximum achievable rate are investigated.

The use of N cognitive relays to assist primary and secondary transmissions in a time-slotted cognitive setting with one primary user (PU) and one secondary user (SU) is investigated. An overlapped spectrum sensing strategy is proposed for channel sensing, where the SU senses the channel for τ seconds from the beginning of the time slot and the cognitive relays sense the channel for 2τ seconds from the beginning of the time slot, thus providing the SU with an intrinsic priority over the relays. The relays sense the channel over the interval [0, τ] to detect primary activity and over the interval [τ, 2τ] to detect secondary activity. The relays help both the PU and SU to deliver their undelivered packets and transmit when both are idle. An optimization-based formulation with quality of service constraints involving queueing delay is studied. The results show the benefits of relaying and its ability to enhance both primary and secondary performance, especially in the case of no direct link between the PU and the SU transmitters and their respective receivers. Three packet decoding strategies at the relays are also investigated and their performance is compared.

In this paper, we propose a cognitive protocol that involves cooperation between the primary and secondary users. In addition to its own queue, the secondary user (SU) has a queue to store, and then relay, the undelivered primary packets. When the primary queue is nonempty, the SU remains idle and attempts to decode the primary packet. When the primary queue is empty, the SU splits the total channel bandwidth into two orthogonal subbands and assigns each to a queue probabilistically. We show the advantage of the proposed protocol over the prioritized cognitive relaying (PCR) protocol in which the SU assigns a priority in transmission to the primary packets over its own packets. We present two problem formulations, one based on throughput and the other on delay. Both optimization problems are shown to be linear programs for a given bandwidth assignment. Numerical results demonstrate the benefits of the proposed protocol.

In this paper, a multiple-access wireless network consisting of two transmitters and one receiver is considered. The transmitters can access the same channel simultaneously and the receiver performs successive interference cancellation (SIC) to decode the messages from both senders. A two-dimensional Markov chain is used to model the medium access control layer behavior of the system, where the state represents the queue length of the transmitters. In this model a general number of packets can be transmitted from any user in a single time slot. A probabilistic cross-layer scheme is proposed to regulate the transmission process between both senders and the receiver. The proposed scheme probabilistically selects the number of packets transmitted from each user and the SIC decoding order at the receiver in order to achieve minimum total average packet delay while satisfying the power constraints for each transmitter. The problem is formulated as a constrained optimization problem then transformed it to a set of convex feasibility problems that can be solved efficiently using the bisection algorithm.

In this paper, we examine a cognitive spectrum access scheme in which a secondary user exploits the primary feedback information. We consider an overlay model in which the secondary user accesses the channel by certain access probabilities that are function of the spectrum sensing metric. In setting our problem, we assume that the secondary user can receive the primary link's feedback automatic repeat request (ARQ), but through an erasure channel. This means that the primary feedback may either be received correctly or is erased with a certain erasure probability. We study the cognitive radio network from a queuing theory point of view. Access probabilities are determined by solving a secondary throughput maximization problem subject to a constraint on the primary queues' stability. Fortunately, our problem is convex and can be solved using standard optimization techniques. Our scheme yields improved results in the secondary throughput than the non-feedback based access scheme attributed to the efficient utilization of the primary user's unerased feedback messages.

In this paper, we study band allocation of Msbuffered secondary users (SUs) to Mporthogonal primary licensed bands, where each primary band is assigned to one primary user (PU). Each SU is assigned to one of the available primary bands with a certain probability designed to satisfy some specified quality of service (QoS) requirements for the SUs. In the proposed system, only one SU is assigned to a particular band. The optimization problem used to obtain the stability region's envelope (closure) is shown to be a linear program. We compare the stability region of the proposed system with that of a system where each SU chooses a band randomly with some assignment probability. We also compare with a fixed (deterministic) assignment system, where only one SU is assigned to one of the primary bands all the time. We prove the advantage of the proposed system over the other systems.

We consider a cognitive setting in which a secondary user tries to opportunistically access a primary channel. Due to the large distance between the secondary source and its destination, the cognitive link involves a relay to forward the secondary data packets to the destination. Since the secondary relay is assumed to be half-duplex, the source and relay operate at exclusive time slots. We obtain the optimal scheduling of the source-relay and relay-destination links in addition to the optimal spectrum sensing parameters. The objective is to minimize the end-to-end secondary queueing delay subject to a constraint on the detection probability of the primary signal and such that the queues at both the source and the relay are stable. We present numerical results that show the system's performance and how it depends on the various parameters.

In this paper, we consider a sequential binary hypothesis testing framework in wireless sensor networks. We study the effect of sensor censoring on network performance in terms of the average error probability and average number of observations required until a global decision is made. The detection process is mathematically modeled as a random walk process with two absorbing barriers. We resort to Chernoff bound in order to find upper bounds on the error probabilities and the average stopping time. The main contribution of this paper is to prove that in a sequential binary hypothesis network where sensors send their hard decisions to the fusion center, censoring can enhance the network performance in comparison to non-censoring networks in certain SNR regimes. Numerical evaluation is provided to illustrate the gains achieved through censoring.

This paper proposes a cooperation protocol between a secondary user (SU) and a primary user (PU) which dedicates a free frequency subband for the SU if cooperation results in energy saving. Time is slotted and users are equipped with buffers. Under the proposed protocol, the PU releases portion of its bandwidth for secondary transmission. Moreover, it assigns a portion of the time slot duration for the SU to relay primary packets and achieve a higher successful packet reception probability at the primary receiver. We assume that the PU has three states: idle, forward, and retransmission states. At each of these states, the SU accesses the channel with adaptive transmission parameters. The PU cooperates with the SU if and only if the achievable average number of transmitted primary packets per joule is higher than the number of transmitted packets per joule when it operates alone. The numerical results show the beneficial gains of the proposed cooperative cognitive protocol.

In this paper, we consider a time-slotted cognitive radio (CR) setting with buffered and energy harvesting primary and CR users. At the beginning of each time slot, the CR user probabilistically chooses the spectrum sensing duration from a predefined set. If the primary user (PU) is sensed to be inactive, the CR user accesses the channel immediately. The CR user optimizes the sensing duration probabilities in order to maximize its mean data service rate with constraints on the stability of the primary and cognitive queues. The optimization problem is split into two subproblems. The first is a linear-fractional program, and the other is a linear program. Both subproblems can be solved efficiently.

In this paper, an iterative blind estimator for fractional carrier frequency offset (CFO) in orthogonal frequency division multiplexing (OFDM) systems is proposed. The estimator utilizes the null subcarriers transmitted at the edge of the spectrum and does not require any training. In addition, the proposed estimator does not require any prior knowledge of the frequency response of the channel. The problem is formulated using a state-space model, and an extended Kalman filter (EKF) is employed to estimate the CFO iteratively. Simulation results illustrate the enhanced ability of the proposed algorithm, relative to the existing approaches, to estimate and track the CFO even in the presence of high Doppler.

We consider a secondary node with fixed energy budget per frame aiming at exploiting the time intervals of primary inactivity. Although a long sensing duration leads to better primary protection, it reduces the time and energy left for the secondary transmission. We seek to exploit the knowledge of the cross channel state information (CCSI) between the secondary transmitter and the primary receiver in order to minimize the required sensing duration, thereby increasing the secondary time and energy for transmission leading to an increase in his throughput. The optimal sensing duration is derived and the benefit of exploiting the cross channel state information is substantiated.

We consider a cognitive radio setting in which a relay-assisted secondary link employs cooperative beamforming to enhance its throughput and to provide protection to the primary receiver from interference. We assume the presence of infinite buffers at both the primary and secondary transmitters and characterize the maximum stable throughput region exactly using the dominant system approach. Numerical examples are provided to give insights into the impact of power control on the stability region.

In this paper, we examine a cognitive spectrum access scheme in which secondary users exploit the primary feedback information. We consider an overlay secondary network employing a random access scheme in which secondary users access the channel by certain access probabilities that are functions of the spectrum sensing metric. In setting our problem, we assume that secondary users can eavesdrop on the primary link's feedback. We study the cognitive radio network from a queuing theory point of view. Access probabilities are determined by solving a secondary throughput maximization problem subject to a constraint on the primary queues' stability. First, we formulate our problem which is found to be non-convex. Yet, we solve it efficiently by exploiting the structure of the secondary throughput equation. Our scheme yields improved results in, both, the secondary user throughput and the primary user packet delay as compared to the scheme where no feedback information is exploited. In addition, it comes very close to the optimal genie-aided scheme in which secondary users act upon the presumed perfect knowledge of the primary users' activity.

We investigate a cognitive radio system with two secondary users who can cooperate with the primary user in relaying its packets to the primary receiver. In addition to its own queue, each secondary user has a queue to keep the primary packets that are not received correctly by the primary receiver. The secondary users accept the unreceived primary packets with a certain probability and transmit randomly from either of their queues if both are nonempty. These probabilities are optimized to expand the maximum stable throughput region of the system. Moreover, we suggest a secondary multiple access scheme in which one secondary user senses the channel for τ seconds from the beginning of the time slot and transmits if the channel is found to be free. The other secondary user senses the channel over the period [0, 2τ] to detect the possible activity of the primary user and the first-ranked secondary user. It transmits, if possible, starting after 2τ seconds from the beginning of the time slot. It compensates for the delayed transmission by increasing its transmission rate so that it still transmits one packet during the time slot. We show the potential advantage of this ordered system over the conventional random access system. We also show the benefit of cooperation in enhancing the network's throughput.

We consider a time-slotted primary system where both the primary channel and primary activity are modeled as two independent two-state Markov chains. The primary transmitter can be idle or busy, whereas the channel can be in erasure or not. Moreover, the sensing channel between the primary transmitter and secondary transmitter is modeled as a two-state Markov chain to represent two levels of sensing reliability. At the beginning of each time slot, the secondary transmitter may remain idle, transmit directly, or probe the channel and access the channel only if it is sensed to be free. At the end of the slot the secondary transmitter overhears the ARQ feedback from the primary receiver, which is used to update its belief regarding primary activity, primary channel state, and sensing channel state. We devise optimal transmission strategies for the cognitive radio so as to maximize secondary throughput with the primary throughput guaranteed to be above a certain specified value. The optimization accounts for the instantaneous reward and also the expected future reward given secondary action.

We consider a random access primary network. At the beginning of each time slot, a number of secondary users sense the channel and make an access decision based on the spectrum sensing outcome and the channel state information (CSI). Specifically, the channel is accessed by a secondary transmitter with a probability that depends on both the sensing metric and the gain or signal-to-noise-ratio (SNR) of the channel between the transmitter and its respective receiver. Spectrum sensing operates in a “soft” mode where the sensing metric is used directly rather than making a binary decision concerning primary activity. We consider backlogged secondary users and primary users with infinite queues. The secondary access probabilities are obtained via solving an optimization problem designed to maximize the secondary throughput given a constraint on primary queue stability. The problem is shown to be convex and, hence, the global optimum can be obtained efficiently. Numerical results reveal a significant performance improvement in the secondary throughout with stable primary queues over the use of spectrum sensing with conventional detection or the implementation of sensing alone without making use of the CSI information.

We consider a secondary user with energy harvesting capability. We design access schemes for the secondary user which incorporate random spectrum sensing and random access, and which make use of the primary automatic repeat request (ARQ) feedback. The sensing and access probabilities are obtained such that the secondary throughput is maximized under the constraints that both the primary and secondary queues are stable and that the primary queueing delay is kept lower than a specified value needed to guarantee a certain quality of service (QoS) for the primary user. We consider spectrum sensing errors and assume multipacket reception (MPR) capabilities. Numerical results are presented to show the enhanced performance of our proposed system over a random access system, and to demonstrate the benefit of leveraging the primary feedback.

Successful spectrum sharing in a cognitive radio network depends on the correct and quick detection of primary activity. Cooperative spectrum sensing is therefore suggested to enhance the reliability of such detection. However, it renders another significant problem of increased detection delay and traffic burden. Moreover, efficient schemes for multi-sensor data fusion should be designed. In this paper, we employ sequential detection scheme together with ordered transmissions from cognitive detectors. We derive two sequential schemes, one that is capable of achieving the minimum probability of error, and another that trades-off performance with delay. For the latter we derive expressions for the likelihood functions of ordered observations and compute the thresholds via backward induction. Simulation results demonstrate the relative performance of the approaches proposed in the paper.

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 user's 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.

We consider a wireless communication scenario with K source-destination pairs communicating through several half-duplex amplify-and-forward relays. We design the relay beamforming matrices by minimizing the total power transmitted from all the relays subject to quality of service constraints on the received signal to interference-plus-noise ratio at each destination node. We propose a novel method for solving the resulting nonconvex optimization problem in which the problem is decomposed into a group of second-order cone programs (SOCPs) parameterized by K real parameters. Grid search or nested bisection can be used to search for the optimal values of these parameters. We provide numerical simulations showing the superior performance of the proposed algorithms compared to earlier suboptimal approximations and their ability to approach the globally optimal solution of the non-convex problem.

Spacecraft-to-ground bistatic radar provides a straightforward method for surveying planetary surfaces on scales of importance to landers and rovers. Centimeter wavelengths, currently in use for deep-space telecommunications, interact with surface structure of similar to somewhat larger scales. For the quasi-specular component of scattering and for surfaces uniformly illuminated by monochromatic signals from an orbiting or flyby vehicle, the echo Doppler dispersion is proportional to the root mean square (rms) surface slope. When the specular condition occurs within 10°-20° of the Brewster angle, the surface dielectric constant can be derived from relative echo power measured simultaneously in orthogonal polarizations and the Fresnel reflection laws. Cross spectra, computed from outputs of the orthogonally polarized receivers, may be used to calculate a complete description of the polarization properties of the scattered fields. Application to planetary studies requires accurate amplitude and phase calibration of the polarization channels, including correction for any leakage between the two receiving paths, such as from imperfectly isolated antenna feeds. We illustrate these techniques using Mars Express results from “Stealth” (Medusae Fossae), a region on Mars that has not previously been detected by Earth-based radar, and from a long profile including Acidalia Planitia. Single-location Stealth observations support previous conclusions that the surface is rough and porous (dielectric constant ≈ 1.4). But the longest experiment (in which the specular point was followed for an hour) yields relatively high dielectric constants (2.8), suggesting that the model is incomplete. The surface of Acidalia Planitia has low dielectric constants ( ≈2.6) over 60-90 W at 50 N and higher values (≈3.6) as the specular point moves south and crosses the equator.

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.

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.

We consider the effects of spectrum sensing errors on the performance of cognitive radio networks from a queueing theory point of view. In order to alleviate the negative effects of those errors, a novel design of spectrum access mechanism is proposed. This design is based on the observation that, in a binary hypothesis testing problem, the value of the test statistic can be used as a confidence measure for the test outcome. This value is hence used to specify a channel access probability for the secondary network. The access probabilities as a function of the sensing metric are obtained via solving an optimization problem designed to maximize the secondary service rate given a constraint on primary queue stability. The problem is shown to be convex and, hence, the global optimum can be obtained efficiently. Numerical results reveal a significant performance improvement in the maximum stable throughput of both primary and secondary networks over the conventional technique of making a hard binary decision and then transmitting with a certain probability if the primary is sensed to be inactive.

We investigate power allocation for users in a shared spectrum network. In such a network, the primary (licensed) users communicate under a minimum guaranteed quality of service (QoS) requirements, whereas the secondary users opportunistically access the primary band. Our objective is to find a power control scheme that determines the transmit power for both primary and secondary users so that the overall network throughput is maximized while maintaining the quality of service of the primary users greater than a specified minimum limit. In the assumed model, no interference cancellation is done at the receivers resulting in a non-convex optimization problem. It has been shown previously that binary power control almost always achieves the global optimum solution when no QoS constraints are imposed. This is not necessarily the case in our scenario, however. We introduce a distributed algorithm for "ternary" power allocation to be used when individual measurements are available at each node. We show via simulations the relative efficiency of the proposed algorithm compared to previously suggested ones. If a central controller exists with available information about the system parameters, we enhance the performance of the proposed algorithm through an iterative geometric programming (GP) algorithm and prove its convergence to a better solution than ternary power allocation.

In many hybrid wireless sensor networks' applications, sensor nodes are deployed in hostile environments where trusted and un-trusted nodes co-exist. In anchor-based hybrid networks, it becomes important to allow trusted nodes to gain full access to the location information transmitted in beacon frames while, at the same time, prevent un-trusted nodes from using this information. The main challenge is that un-trusted nodes can measure the physical signal transmitted from anchor nodes, even if these nodes encrypt their transmission. Using the measured signal strength, un-trusted nodes can still tri-laterate the location of anchor nodes. In this paper, we propose HyberLoc, an algorithm that provides anchor physical layer location privacy in anchor-based hybrid sensor networks. The idea is for anchor nodes to dynamically change their transmission power following a certain probability distribution, degrading the localization accuracy at un-trusted nodes while maintaining high localization accuracy at trusted nodes. Given an average power constraint, our analysis shows that the discretized exponential distribution is the distribution that maximizes location uncertainty at the un-trusted nodes. Detailed evaluation through analysis, simulation, and implementation shows that HyperLoc gives trusted nodes up to 3.5 times better localization accuracy as compared to un-trusted nodes.

In this paper we investigate admission control and power allocation for cognitive radios in an underlay network. We consider the problem of maximizing the number of supported secondary links under their minimum QoS requirements without violating the maximum tolerable interference on primary receivers in a cellular network. An optimal solution to our problem is shown in previous works to be NP-hard. We propose an efficient distributed algorithm with reasonable complexity that provides results close to the optimum solution without requiring neither a large amount of signaling nor a wide range of information about the system parameters. Our algorithm is compared with previously proposed algorithms to demonstrate its relative efficiency.

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.

We consider the design of cognitive medium access control (MAC) protocols enabling an unlicensed (secondary) transmitter-receiver pair to communicate over the idle periods of a set of licensed channels, i.e., the primary network. The objective is to maximize data throughput while maintaining the synchronization between secondary users and avoiding interference with licensed (primary) users. No statistical information about the primary traffic is assumed to be available a-priori to the secondary user. We investigate two distinct sensing scenarios. In the first, the secondary transmitter is capable of sensing all the primary channels, whereas it senses one channel only in the second scenario. In both cases, we propose MAC protocols that efficiently learn the statistics of the primary traffic online. Our simulation results demonstrate that the proposed blind protocols asymptotically achieve the throughput obtained when prior knowledge of primary traffic statistics is available.

Valid application of the Kirchhoff approximation (KA) for scattering from rough surfaces requires that the surface radius of curvature exceed approximately the electromagnetic wavelength /spl lambda/. Fractal surface models have characteristic features on arbitrarily small scales, thereby posing problems in application of the electromagnetic boundary conditions in general as well as in the evaluation of surface radius of curvature pertinent to KA. Experiments and numerical simulations show variations in scattering behavior that are consistent with scattering from progressively smoother surfaces with increasing wavelength, demonstrating surface smoothing effects in the wave-surface interaction. We hypothesize control of KA scattering from fractal surfaces by an effective average radius of curvatureas a function of the smallest lateral scale /spl Delta/x contributing to scattering at /spl lambda/. Solution of=/spl lambda/ for /spl lambda/ is one possible method for approximating the limit of KA validity, assuming that /spl Delta/x[/spl lambda/] is known. Investigation of the validity of KA for the calculation of scattering from perfectly conducting Weierstrass-Mandelbrot and fractional Brownian process fractal surface models shows that for both models the region of applicability of KA grows with increases in /spl lambda/ and the Hurst exponent H controlling large-scale roughness. Numerical simulations using the method of moments demonstrate the dependence of /spl Delta/x on /spl lambda/ and the surface parameters.