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We present a symmetry-agnostic topology optimization framework for photonic-crystal structures based on computation of the photonic density of states in a manner analogous to $\Gamma$-point integration. We provide a generalization of the approach that allows for computations at different scales with the additional scales being analogous to integration over the full Brillouin zone and to regimes between the two limiting cases of full Brillouin-zone integration and $\Gamma$-point integration, though these other scales do not preserve the symmetry-agnostic nature of the $\Gamma$-point framework. We also demonstrate how our approach can be generalized to the problem of inverting photonic or phononic bandstructures. Finally, we show that at the symmetry-agnostic scale analogous to $\Gamma$-point integration, we can recover a known two-dimensional photonic crystal for the TM polarization. A key insight of our work is the determination of the minimum supercell size and the minimum precision to which the frequencies within the photonic bandgap must be sampled in order to observe photonic-crystal structures.

Online transient stability assessment (TSA) is essential for secure and stable power system operations. The growing number of Phasor Measurement Units (PMUs) brings about massive sources of data that can enhance online TSA. However, conventional data-driven methods require large amounts of transient data to correctly assess the transient stability state of a system. In this paper, a new data-driven TSA approach is developed for TSA with fewer data compared to the conventional methods. The data reduction is enabled by learning the dynamic behaviors of the historical transient data using generative and adversarial networks (GAN). This knowledge is used online to predict the voltage time series data after a transient event. A classifier embedded in the generative network deploys the predicted post-contingency data to determine the stability of the system following a fault. The developed GAN-based TSA approach preserves the spatial and temporal correlations that exist in multivariate PMU time series data. Hence, in comparison with the state-of-the-art TSA methods, it achieves a higher assessment accuracy using only one sample of the measured data and a shorter response time. Case studies conducted on the IEEE 118-bus system demonstrate the superior performance of the GAN-based method compared to the conventional data-driven techniques.

The use of unmanned aerial vehicles (UAVs) operating as aerial base stations (BSs) has emerged as a promising solution especially in scenarios requiring rapid deployments (e.g., in the cases of crowded hotspots, sporting events, emergencies, natural disasters) in order to assist the ground BSs. In this paper, an analytical framework is provided to analyze the signal-to-interference-plus-noise ratio (SINR) coverage probability of unmanned aerial vehicle (UAV) assisted cellular networks with clustered user equipments (UEs). Locations of UAVs and ground BSs are modeled as Poison point processes (PPPs), and UEs are assumed to be distributed according to a Poisson cluster process (PCP) around the projections of UAVs on the ground. Initially, the complementary cumulative distribution function (CCDF) and probability density function (PDF) of path losses for both UAV and ground BS tiers are derived. Subsequently, association probabilities with each tier are obtained. SINR coverage probability is derived for the entire network using tools from stochastic geometry. Finally, area spectral efficiency (ASE) of the entire network is determined, and SINR coverage probability expression for a more general model is presented by considering that UAVs are located at different heights. Via numerical results, we have shown that UAV height and path-loss exponents play important roles on the coverage performance. Moreover, coverage probability can be improved with smaller number of UAVs, while better area spectral efficiency is achieved by employing more UAVs and having UEs more compactly clustered around the UAVs.

In cognitive radio systems, employing sensing-based spectrum access strategies, secondary users are required to perform channel sensing in order to detect the activities of primary users. In realistic scenarios, channel sensing occurs with possible errors due to miss-detections and false alarms. As another challenge, time-varying fading conditions in the channel between the secondary transmitter and the secondary receiver have to be learned via channel estimation. In this paper, performance of causal channel estimation methods in correlated cognitive radio channels under imperfect channel sensing results is analyzed, and achievable rates under both channel and sensing uncertainty are investigated. Initially, cognitive radio channel model with channel sensing error and channel estimation is described. Then, using pilot symbols, minimum mean square error (MMSE) and linear-MMSE (L-MMSE) estimation methods are employed at the secondary receiver to learn the channel fading coefficients. Expressions for the channel estimates and mean-squared errors (MSE) are determined, and their dependencies on channel sensing results, and pilot symbol period and energy are investigated. Since sensing uncertainty leads to uncertainty in the variance of the additive disturbance, channel estimation strategies and performance are interestingly shown to depend on the sensing reliability. It is further shown that the L-MMSE estimation method, which is in general suboptimal, performs very close to MMSE estimation. Furthermore, assuming the channel estimation errors and the interference introduced by the primary users as zero-mean and Gaussian distributed, achievable rate expressions of linear modulation schemes and Gaussian signaling are determined. Subsequently, the training period, and data and pilot symbol energy allocations are jointly optimized to maximize the achievable rates for both signaling schemes.

In this paper, throughput and energy efficiency of cognitive multiple-input multiple-output (MIMO) systems operating under quality-of-service (QoS) constraints, interference limitations, and imperfect channel sensing, are studied. It is assumed that transmission power and covariance of the input signal vectors are varied depending on the sensed activities of primary users (PUs) in the system. Interference constraints are applied on the transmission power levels of cognitive radios (CRs) to provide protection for the PUs whose activities are modeled as a Markov chain. Considering the reliability of the transmissions and channel sensing results, a state-transition model is provided. Throughput is determined by formulating the effective capacity. First derivative of the effective capacity is derived in the low-power regime and the minimum bit energy requirements in the presence of QoS limitations and imperfect sensing results are identified. Minimum energy per bit is shown to be achieved by beamforming in the maximal-eigenvalue eigenspace of certain matrices related to the channel matrix. In a special case, wideband slope is determined for more refined analysis of energy efficiency. Numerical results are provided for the throughput for various levels of buffer constraints and different number of transmit and receive antennas. The impact of interference constraints and benefits of multiple-antenna transmissions are determined. It is shown that increasing the number of antennas when the interference power constraint is stringent is generally beneficial. On the other hand, it is shown that under relatively loose interference constraints, increasing the number of antennas beyond a certain level does not lead to much increase in the throughput.

A two-hop wireless communication link in which a source sends data to a destination with the aid of an intermediate relay node is studied. It is assumed that there is no direct link between the source and the destination, and the relay forwards the information to the destination by employing the decode-and-forward scheme. Both the source and intermediate relay nodes are assumed to operate under statistical quality of service (QoS) constraints imposed as limitations on the buffer overflow probabilities. The maximum constant arrival rates that can be supported by this two-hop link in the presence of QoS constraints are characterized by determining the effective capacity of such links as a function of the QoS parameters and signal-to-noise ratios at the source and relay, and the fading distributions of the links. The analysis is performed for both full-duplex and half-duplex relaying. Through this study, the impact upon the throughput of having buffer constraints at the source and intermediate relay nodes is identified. The interactions between the buffer constraints in different nodes and how they affect the performance are studied. The optimal time-sharing parameter in half-duplex relaying is determined, and performance with half-duplex relaying is investigated.

In this paper, we study two-way relay networks (TWRNs) in which two source nodes exchange their information via a relay node indirectly in Rayleigh fading channels. Both Amplify-and-Forward (AF) and Decode-and-Forward (DF) techniques have been analyzed in the TWRN employing a Markov chain model through which the network operation is described and investigated in depth. Automatic Repeat-reQuest (ARQ) retransmission has been applied to guarantee the successful packet delivery. The bit energy consumption and goodput expressions have been derived as functions of transmission rate in a given AF or DF TWRN. Numerical results are used to identify the optimal transmission rates where the bit energy consumption is minimized or the goodput is maximized. The network performances are compared in terms of energy and transmission efficiency in AF and DF modes.

In this paper, secure transmission of information over fading broadcast channels is studied in the presence of statistical queueing constraints. Effective capacity is employed as a performance metric to identify the secure throughput of the system, i.e., effective secure throughput. It is assumed that perfect channel side information (CSI) is available at both the transmitter and the receivers. Initially, the scenario in which the transmitter sends common messages to two receivers and confidential messages to one receiver is considered. For this case, effective secure throughput region, which is the region of constant arrival rates of common and confidential messages that can be supported by the buffer-constrained transmitter and fading broadcast channel, is defined. It is proven that this effective throughput region is convex. Then, the optimal power control policies that achieve the boundary points of the effective secure throughput region are investigated and an algorithm for the numerical computation of the optimal power adaptation schemes is provided. Subsequently, the special case in which the transmitter sends only confidential messages to one receiver, is addressed in more detail. For this case, effective secure throughput is formulated and two different power adaptation policies are studied. In particular, it is noted that opportunistic transmission is no longer optimal under buffer constraints and the transmitter should not wait to send the data at a high rate until the main channel is much better than the eavesdropper channel.

This paper investigates the performance of wireless systems that employ finite-blocklength channel codes for transmission and operate under queueing constraints in the form of limitations on buffer overflow probabilities. A block fading model, in which fading stays constant in each coherence block and change independently between blocks, is considered. It is assumed that channel coding is performed over multiple coherence blocks. An approximate lower bound on the transmission rate is obtained from Feintein's Lemma. This lower bound is considered as the service rate and is incorporated into the effective capacity formulation, which characterizes the maximum constant arrival rate that can be supported under statistical queuing constraints. Performances of variable-rate and fixed-rate transmissions are studied. The optimum error probability for variable rate transmission and the optimum coding rate for fixed rate transmission are shown to be unique. Moreover, the tradeoff between the throughput and the number of blocks over which channel coding is performed is identified., Comment: submitted to ICC 2011

In this paper, two-hop communication between a source and a destination with the aid of an intermediate relay node is considered. Both the source and intermediate relay node are assumed to operate under statistical quality of service (QoS) constraints imposed as limitations on the buffer overflow probabilities. It is further assumed that the nodes send the information at fixed power levels and have perfect channel side information. In this scenario, the maximum constant arrival rates that can be supported by this two-hop link are characterized by finding the effective capacity. Through this analysis, the impact upon the throughput of having buffer constraints at the source and intermediate-hop nodes is identified., Comment: submitted to ICC 2011

In the spectrum-sharing technology, a secondary user may utilize the primary user's licensed band as long as its interference to the primary user is below a tolerable value. In this paper, we consider a scenario in which a secondary user is operating in the presence of both a primary user and an eavesdropper. Hence, the secondary user has both interference limitations and security considerations. In such a scenario, we study the secrecy capacity limits of opportunistic spectrum-sharing channels in fading environments and investigate the optimal power allocation for the secondary user under average and peak received power constraints at the primary user with global channel side information (CSI). Also, in the absence of the eavesdropper's CSI, we study optimal power allocation under an average power constraint and propose a suboptimal on/off power control method.

In this paper, a cognitive relay channel is considered, and amplify-and-forward (AF) relay beamforming designs in the presence of an eavesdropper and a primary user are studied. Our objective is to optimize the performance of the cognitive relay beamforming system while limiting the interference in the direction of the primary receiver and keeping the transmitted signal secret from the eavesdropper. We show that under both total and individual power constraints, the problem becomes a quasiconvex optimization problem which can be solved by interior point methods. We also propose two sub-optimal null space beamforming schemes which are obtained in a more computationally efficient way.

In this paper, the average successful throughput, i.e., goodput, of a coded 3-node cooperative network is studied in a Rayleigh fading environment. It is assumed that a simple automatic repeat request (ARQ) technique is employed in the network so that erroneously received codeword is retransmitted until successful delivery. The relay is assumed to operate in either amplify-and-forward (AF) or decode-and-forward (DF) mode. Under these assumptions, retransmission mechanisms and protocols are described, and the average time required to send information successfully is determined. Subsequently, the goodput for both AF and DF relaying is formulated. The tradeoffs and interactions between the goodput, transmission rates, and relay location are investigated and optimal strategies are identified., Comment: 7 pages, 10 figures

Effective capacity, which provides the maximum constant arrival rate that a given service process can support while satisfying statistical delay constraints, is analyzed in a multiuser scenario. In particular, the effective capacity region of fading multiple access channels (MAC) in the presence of quality of service (QoS) constraints is studied. Perfect channel side information (CSI) is assumed to be available at both the transmitters and the receiver. It is initially assumed the transmitters send the information at a fixed power level and hence do not employ power control policies. Under this assumption, the performance achieved by superposition coding with successive decoding techniques is investigated. It is shown that varying the decoding order with respect to the channel states can significantly increase the achievable throughput region. In the two-user case, the optimal decoding strategy is determined for the scenario in which the users have the same QoS constraints. The performance of orthogonal transmission strategies is also analyzed. It is shown that for certain QoS constraints, time-division multiple-access (TDMA) can achieve better performance than superposition coding if fixed successive decoding order is used at the receiver side. In the subsequent analysis, power control policies are incorporated into the transmission strategies. The optimal power allocation policies for any fixed decoding order over all channel states are identified. For a given variable decoding order strategy, the conditions that the optimal power control policies must satisfy are determined, and an algorithm that can be used to compute these optimal policies is provided.

In this paper, wireless systems operating under queueing constraints in the form of limitations on the buffer violation probabilities are considered. The throughput under such constraints is captured by the effective capacity formulation. It is assumed that finite blocklength codes are employed for transmission. Under this assumption, a recent result on the channel coding rate in the finite blocklength regime is incorporated into the analysis and the throughput achieved with such codes in the presence of queueing constraints and decoding errors is identified. Performance of different transmission strategies (e.g., variable-rate, variable-power, and fixed-rate transmissions) is studied. Interactions between the throughput, queueing constraints, coding blocklength, decoding error probabilities, and signal-to-noise ratio are investigated and several conclusions with important practical implications are drawn.

In this paper, collaborative use of relays to form a beamforming system and provide physical-layer security is investigated. In particular, decode-and-forward (DF) and amplify-and-forward (AF) relay beamforming designs under total and individual relay power constraints are studied with the goal of maximizing the secrecy rates when perfect channel state information (CSI) is available. In the DF scheme, the total power constraint leads to a closed-form solution, and in this case, the optimal beamforming structure is identified in the low and high signal-to-noise ratio (SNR) regimes. The beamforming design under individual relay power constraints is formulated as an optimization problem which is shown to be easily solved using two different approaches, namely semidefinite programming and second-order cone programming. A simplified and suboptimal technique which reduces the computation complexity under individual power constraints is also presented. In the AF scheme, not having analytical solutions for the optimal beamforming design under both total and individual power constraints, an iterative algorithm is proposed to numerically obtain the optimal beamforming structure and maximize the secrecy rates. Finally, robust beamforming designs in the presence of imperfect CSI are investigated for DF-based relay beamforming, and optimization frameworks are provided, Comment: The material in this paper was submitted in part at arXiv:0910.4132

In this paper, the performance of cognitive transmission under quality of service (QoS)constraints and interference limitations is studied. Cognitive secondary users are assumed to initially perform sensing over multiple frequency bands (or equivalently channels) to detect the activities of primary users. Subsequently, they perform transmission in a single channel at variable power and rates depending on the channel sensing decisions and the fading environment. A state transition model is constructed to model this cognitive operation. Statistical limitations on the buffer lengths are imposed to take into account the QoS constraints of the cognitive secondary users. Under such QoS constraints and limitations on the interference caused to the primary users, the maximum throughput is identified by finding the effective capacity of the cognitive radio channel. Optimal power allocation strategies are obtained and the optimal channel selection criterion is identified. The intricate interplay between effective capacity, interference and QoS constraints, channel sensing parameters and reliability, fading, and the number of available frequency bands is investigated through numerical results.

In this paper, performance of cognitive transmission over time-selective flat fading channels is studied under quality of service (QoS) constraints and channel uncertainty. Cognitive secondary users (SUs) are assumed to initially perform channel sensing to detect the activities of the primary users, and then attempt to estimate the channel fading coefficients through training. Energy detection is employed for channel sensing, and different minimum mean-square-error (MMSE) estimation methods are considered for channel estimation. In both channel sensing and estimation, erroneous decisions can be made, and hence, channel uncertainty is not completely eliminated. In this setting, performance is studied and interactions between channel sensing and estimation are investigated. Following the channel sensing and estimation tasks, SUs engage in data transmission. Transmitter, being unaware of the channel fading coefficients, is assumed to send the data at fixed power and rate levels that depend on the channel sensing results. Under these assumptions, a state-transition model is constructed by considering the reliability of the transmissions, channel sensing decisions and their correctness, and the evolution of primary user activity which is modeled as a two-state Markov process. In the data transmission phase, an average power constraint on the secondary users is considered to limit the interference to the primary users, and statistical limitations on the buffer lengths are imposed to take into account the QoS constraints of the secondary traffic. The maximum throughput under these statistical QoS constraints is identified by finding the effective capacity of the cognitive radio channel. Numerical results are provided for the power and rate policies.

In this paper, pilot-symbol-assisted transmission in cognitive radio systems over time selective flat fading channels is studied. It is assumed that causal and noncausal Wiener filter estimators are used at the secondary receiver with the aid of training symbols to obtain the channel side information (CSI) under an interference power constraint. Cognitive radio model is described together with detection and false alarm probabilities determined by using a Neyman-Person detector for channel sensing. Subsequently, for both filters, the variances of estimate errors are calculated from the Doppler power spectrum of the channel, and achievable rate expressions are provided considering the scenarios which are results of channel sensing. Numerical results are obtained in Gauss-Markov modeled channels, and achievable rates obtained by using causal and noncausal filters are compared and it is shown that the difference is decreasing with increasing signal-to-noise ratio (SNR). Moreover, the optimal probability of detection and false alarm values are shown, and the tradeoff between these two parameters is discussed. Finally, optimal power distributions are provided.

In this paper, collaborative use of relays to form a beamforming system with the aid of perfect channel state information (CSI) and to provide communication in physicallayer security between a transmitter and two receivers is investigated. In particular, we describe decode-and-forward based null space beamforming schemes and optimize the relay weights jointly to obtain the largest secrecy rate region. Furthermore, the optimality of the proposed schemes is investigated by comparing them with the outer bound secrecy rate region, Comment: Proc. of the IEEE Wireless Communications and Networking Conference (WCNC) Sydney, Austria, April 2010

In this paper, cognitive transmission under quality of service (QoS) constraints is studied. In the cognitive radio channel model, it is assumed that both the secondary receiver and the secondary transmitter know the channel fading coefficients perfectly and optimize the power adaptation policy under given constraints, depending on the channel activity of the primary users, which is determined by channel sensing performed by the secondary users. The transmission rates are equal to the instantaneous channel capacity values. A state transition model with four states is constructed to model this cognitive transmission channel. Statistical limitations on the buffer lengths are imposed to take into account the QoS constraints. The maximum throughput under these statistical QoS constraints is identified by finding the effective capacity of the cognitive radio channel. The impact upon the effective capacity of several system parameters, including the channel sensing duration, detection threshold, detection and false alarm probabilities, and QoS parameters, is investigated.

In this paper, the secure transmission of information over an ergodic fading channel is investigated in the presence of statistical quality of service (QoS) constraints. We employ effective capacity, which provides the maximum constant arrival rate that a given process can support while satisfying statistical delay constraints, to measure the secure throughput of the system, i.e., effective secure throughput. We assume that the channel side information (CSI) of the main channel is available at the transmitter side. Depending on the availability of the CSI of the eavesdropper channel, we obtain the corresponding optimal power control policies that maximize the effective secure throughput. In particular, when the CSI of the eavesdropper channel is available at the transmitter, the transmitter can no longer wait for transmission when the main channel is much better than the eavesdropper channel due to the introduction of QoS constraints. Moreover, the CSI of the eavesdropper channel becomes useless as QoS constraints become stringent.

In this paper, the fading broadcast channel with confidential messages is studied in the presence of statistical quality of service (QoS) constraints in the form of limitations on the buffer length. We employ the effective capacity formulation to measure the throughput of the confidential and common messages. We assume that the channel side information (CSI) is available at both the transmitter and the receivers. Assuming average power constraints at the transmitter side, we first define the effective secure throughput region, and prove that the throughput region is convex. Then, we obtain the optimal power control policies that achieve the boundary points of the effective secure throughput region.

In this paper, collaborative use of relays to form a beamforming system and provide physical-layer security is investigated. In particular, amplify-and-forward (AF) relay beamforming designs under total and individual relay power constraints are studied with the goal of maximizing the secrecy rates when perfect channel state information (CSI) is available. In the AF scheme, not having analytical solutions for the optimal beamforming design under both total and individual power constraints, an iterative algorithm is proposed to numerically obtain the optimal beamforming structure and maximize the secrecy rates. Robust beamforming designs in the presence of imperfect CSI are investigated for decode-and-forward (DF) based relay beamforming, and optimization frameworks are provided., Comment: Proc. of the 44th Annual Conference on Information Sciences and Systems, Princeton, March 2010

In this paper, we have studied the energy efficiency of cooperative networks operating in either the fixed Amplifyand- Forward (AF) or the selective Decode-and-Forward (DF) mode. We consider the optimization of the M-ary quadrature amplitude modulation (MQAM) constellation size to minimize the bit energy consumption under given bit error rate (BER) constraints. In the computation of the energy expenditure, the circuit, transmission, and retransmission energies are taken into account. The link reliabilities and retransmission probabilities are determined through the outage probabilities under the Rayleigh fading assumption. Several interesting observations with practical implications are made. It is seen that while large constellations are preferred at small transmission distances, constellation size should be decreased as the distance increases; the cooperative gain is computed to compare direct transmission and cooperative transmission., Comment: Proc. IEEE WCNC2010, Sydney, Australia, April, 2010

Effective capacity, which provides the maximum constant arrival rate that a given service process can support while satisfying statistical delay constraints, is analyzed in a multiuser scenario. In particular, we study the achievable effective capacity region of the users in multiaccess fading channels (MAC) in the presence of quality of service (QoS) constraints. We assume that channel side information (CSI) is available at both the transmitters and the receiver, and superposition coding technique with successive decoding is used. When the power is fixed at the transmitters, we show that varying the decoding order with respect to the channel state can significantly increase the achievable throughput region. For a two-user case, we obtain the optimal decoding strategy when the users have the same QoS constraints. Meanwhile, it is shown that time-division multiple-access (TDMA) can achieve better performance than superposition coding with fixed successive decoding order at the receiver side for certain QoS constraints. For power and rate adaptation, we determine the optimal power allocation policy with fixed decoding order at the receiver side. Numerical results are provided to demonstrate our results.

In this paper, collaborative use of relays to form a beamforming system with the aid of perfect channel state information (CSI) and to provide physical-layer security is investigated. In particular, a decode-and-forward-based relay beamforming design subject to total and individual relay power constraints is studied with the goal of maximizing the secrecy rate. It is shown that the total power constraint leads to a closed-form solution. The design under individual relay power constraints is formulated as an optimization problem which is shown to be easily solved using two different approaches, namely semidefinite programming and second-order cone programming. Furthermore, a simplified and suboptimal technique which reduces the computation complexity under individual power constraints is presented.

Secrecy capacity of a multiple-antenna wiretap channel is studied in the low signal-to-noise ratio (SNR) regime. Expressions for the first and second derivatives of the secrecy capacity with respect to SNR at SNR = 0 are derived. Transmission strategies required to achieve these derivatives are identified. In particular, it is shown that it is optimal in the low-SNR regime to transmit in the maximal-eigenvalue eigenspace of Phi = H_m* H_m - N_m/N_e H_e* H_e where H_m and H_e denote the channel matrices associated with the legitimate receiver and eavesdropper, respectively, and N_m and N_e are the noise variances at the receiver and eavesdropper, respectively. Energy efficiency is analyzed by finding the minimum bit energy required for secure and reliable communications, and the wideband slope. Increased bit energy requirements under secrecy constraints are quantified. Finally, the impact of fading is investigated, and the benefits of fading in terms of energy efficiency are shown.

The performance of multiple-input multiple-output wireless systems is investigated in the presence of statistical queueing constraints. Queuing constraints are imposed as limitations on buffer violation probabilities. The performance under such constraints is captured through the effective capacity formulation. A detailed analysis of the effective capacity is carried out in the low-power, wideband, and high--signal-to-noise ratio (SNR) regimes. In the low-power analysis, expressions for the first and second derivatives of the effective capacity with respect to SNR at SNR= 0 are obtained under various assumptions on the degree of channel state information at the transmitter. Transmission strategies that are optimal in the sense of achieving the first and second derivatives are identified. It is shown that while the first derivative does not get affected by the presence of queueing constraints, the second derivative gets smaller as the constraints become more stringent. Through the energy efficiency analysis, this is shown to imply that the minimum bit energy requirements do not change with more strict limitations but the wideband slope diminishes. Similar results are obtained in the wideband regime if rich multipath fading is being experienced. On the other hand, sparse multipath fading with bounded number of degrees of freedom is shown to increase the minimum bit energy requirements in the presence of queueing constraints. Following the low-SNR study, the impact of buffer limitations on the high-SNR performance is quantified by analyzing the high-SNR slope and the power offset in Rayleigh fading channels. Finally, numerical results are provided to illustrate the theoretical findings., Comment: A shorter version is presented at the 2009 Allerton Conference

Energy efficiency of fixed-rate transmissions is studied in the presence of queueing constraints and channel uncertainty. It is assumed that neither the transmitter nor the receiver has channel side information prior to transmission. The channel coefficients are estimated at the receiver via minimum mean-square-error (MMSE) estimation with the aid of training symbols. It is further assumed that the system operates under statistical queueing constraints in the form of limitations on buffer violation probabilities. The optimal fraction of power allocated to training is identified. Spectral efficiency--bit energy tradeoff is analyzed in the low-power and wideband regimes by employing the effective capacity formulation. In particular, it is shown that the bit energy increases without bound in the low-power regime as the average power vanishes. A similar conclusion is reached in the wideband regime if the number of noninteracting subchannels grow without bound with increasing bandwidth. On the other hand, it is proven that if the number of resolvable independent paths and hence the number of noninteracting subchannels remain bounded as the available bandwidth increases, the bit energy diminishes to its minimum value in the wideband regime. For this case, expressions for the minimum bit energy and wideband slope are derived. Overall, energy costs of channel uncertainty and queueing constraints are identified, and the impact of multipath richness and sparsity is determined.

In this paper, we have considered the optimization of the $M$-ary quadrature amplitude modulation (MQAM) constellation size to minimize the bit energy consumption under average bit error rate (BER) constraints. In the computation of the energy expenditure, the circuit, transmission, and retransmission energies are taken into account. A combined log-normal shadowing and Rayleigh fading model is employed to model the wireless channel. The link reliabilities and retransmission probabilities are determined through the outage probabilities under log-normal shadowing effects. Both single-hop and multi-hop transmissions are considered. Through numerical results, the optimal constellation sizes are identified. Several interesting observations with practical implications are made. It is seen that while large constellations are preferred at small transmission distances, constellation size should be decreased as the distance increases. Similar trends are observed in both fixed and variable transmit power scenarios. We have noted that variable power schemes can attain higher energy-efficiencies. The analysis of energy-efficient modulation design is also conducted in multi-hop linear networks. In this case, the modulation size and routing paths are jointly optimized, and the analysis of both the bit energy and delay experienced in the linear network is provided., Comment: appeared at CISS 2009

Error performance of noncoherent detection of on-off frequency shift keying (OOFSK) modulation over fading channels is analyzed when the receiver is equipped with multiple antennas. The analysis is conducted for two cases: 1) the case in which the receiver has the channel distribution knowledge only; and 2) the case in which the receiver perfectly knows the fading magnitudes. For both cases, the maximum a posteriori probability (MAP) detection rule is derived and analytical probability of error expressions are obtained. Numerical and simulation results indicate that for sufficiently low duty cycle values, lower error probabilities with respect to FSK signaling are achieved. Equivalently, when compared to FSK modulation, OOFSK with low duty cycle requires less energy to achieve the same probability of error, which renders this modulation a more energy efficient transmission technique. Also, through numerical results, the impact of number of antennas, antenna correlation, duty cycle values, and unknown channel fading on the performance are investigated., Comment: to appear in the IEEE Transactions on Wireless Communications

In this paper, cognitive transmission under quality of service (QoS) constraints is studied. In the cognitive radio channel model, it is assumed that the secondary transmitter sends the data at two different average power levels, depending on the activity of the primary users, which is determined by channel sensing performed by the secondary users. A state-transition model is constructed for this cognitive transmission channel. Statistical limitations on the buffer lengths are imposed to take into account the QoS constraints. The maximum throughput under these statistical QoS constraints is identified by finding the effective capacity of the cognitive radio channel. This analysis is conducted for fixed-power/fixed-rate, fixed-power/variable-rate, and variable-power/variable-rate transmission schemes under different assumptions on the availability of channel side information (CSI) at the transmitter. The impact upon the effective capacity of several system parameters, including channel sensing duration, detection threshold, detection and false alarm probabilities, QoS parameters, and transmission rates, is investigated. The performances of fixed-rate and variable-rate transmission methods are compared in the presence of QoS limitations. It is shown that variable schemes outperform fixed-rate transmission techniques if the detection probabilities are high. Performance gains through adapting the power and rate are quantified and it is shown that these gains diminish as the QoS limitations become more stringent.

Energy efficiency of fixed-rate transmissions is studied in the presence of queueing constraints and channel uncertainty. It is assumed that neither the transmitter nor the receiver has channel side information prior to transmission. The channel coefficients are estimated at the receiver via minimum mean-square-error (MMSE) estimation with the aid of training symbols. It is further assumed that the system operates under statistical queueing constraints in the form of limitations on buffer violation probabilities. The optimal fraction of of power allocated to training is identified. Spectral efficiency--bit energy tradeoff is analyzed in the low-power and wideband regimes by employing the effective capacity formulation. In particular, it is shown that the bit energy increases without bound in the low-power regime as the average power vanishes. On the other hand, it is proven that the bit energy diminishes to its minimum value in the wideband regime as the available bandwidth increases. For this case, expressions for the minimum bit energy and wideband slope are derived. Overall, energy costs of channel uncertainty and queueing constraints are identified.

In this paper, we study the secrecy rates over weak Gaussian interference channels for different transmission schemes. We focus on the low-SNR regime and obtain the minimum bit energy E_b/N_0_min values, and the wideband slope regions for both TDMA and multiplexed transmission schemes. We show that secrecy constraints introduce a penalty in both the minimum bit energy and the slope regions. Additionally, we identify under what conditions TDMA or multiplexed transmission is optimal. Finally, we show that TDMA is more likely to be optimal in the presence of secrecy constraints.

Secrecy capacity of a multiple-antenna wiretap channel is studied in the low signal-to-noise ratio (SNR) regime. Expressions for the first and second derivatives of the secrecy capacity with respect to SNR at SNR = 0 are derived. Transmission strategies required to achieve these derivatives are identified. In particular, it is shown that it is optimal in the low-SNR regime to transmit in the maximum-eigenvalue eigenspace of H_m* H_m - N_m/N_e H_e* H_e where H_m and H_e denote the channel matrices associated with the legitimate receiver and eavesdropper, respectively, and N_m and N_e are the noise variances at the receiver and eavesdropper, respectively. Energy efficiency is analyzed by finding the minimum bit energy required for secure and reliable communications, and the wideband slope. Increased bit energy requirements under secrecy constraints are quantified. Finally, the impact of fading is investigated.

Transmission over wireless fading channels under quality of service (QoS) constraints is studied when only the receiver has channel side information. Being unaware of the channel conditions, transmitter is assumed to send the information at a fixed rate. Under these assumptions, a two-state (ON-OFF) transmission model is adopted, where information is transmitted reliably at a fixed rate in the ON state while no reliable transmission occurs in the OFF state. QoS limitations are imposed as constraints on buffer violation probabilities, and effective capacity formulation is used to identify the maximum throughput that a wireless channel can sustain while satisfying statistical QoS constraints. Energy efficiency is investigated by obtaining the bit energy required at zero spectral efficiency and the wideband slope in both wideband and low-power regimes assuming that the receiver has perfect channel side information (CSI). In both wideband and low-power regimes, the increased energy requirements due to the presence of QoS constraints are quantified. Comparisons with variable-rate/fixed-power and variable-rate/variable-power cases are given. Energy efficiency is further analyzed in the presence of channel uncertainties. The optimal fraction of power allocated to training is identified under QoS constraints. It is proven that the minimum bit energy in the low-power regime is attained at a certain nonzero power level below which bit energy increases without bound with vanishing power.

In this paper, transmission over the additive white Gaussian noise (AWGN) channel, and coherent and noncoherent fading channels using M-ary orthogonal frequency-shift keying (FSK) or on-off frequency-shift keying (OOFSK) is considered. The receiver is assumed to perform hard-decision detection. In this setting, energy required to reliably send one bit of information is investigated. It is shown that for fixed M and duty cycle, bit energy requirements grow without bound as the signal-to-noise ratio (SNR) vanishes. The minimum bit energy values are numerically obtained for different values of M and the duty cycle. The impact of fading on the energy efficiency is identified. Requirements to approach the minimum bit energy of -1.59 dB are determined., Comment: appeared at ISIT 2008

Energy efficiency in fading channels in the presence of Quality of Service (QoS) constraints is studied. Effective capacity, which provides the maximum arrival rate that a wireless channel can sustain while satisfying statistical QoS constraints, is considered. Spectral efficiency--bit energy tradeoff is analyzed in the low-power and wideband regimes by employing the effective capacity formulation, rather than the Shannon capacity. Through this analysis, energy requirements under QoS constraints are identified. The analysis is conducted under two assumptions: perfect channel side information (CSI) available only at the receiver and perfect CSI available at both the receiver and transmitter. In particular, it is shown in the low-power regime that the minimum bit energy required under QoS constraints is the same as that attained when there are no such limitations. However, this performance is achieved as the transmitted power vanishes. Through the wideband slope analysis, the increased energy requirements at low but nonzero power levels in the presence of QoS constraints are determined. A similar analysis is also conducted in the wideband regime, and minimum bit energy and wideband slope expressions are obtained. In this regime, the required bit energy levels are found to be strictly greater than those achieved when Shannon capacity is considered. Overall, a characterization of the energy-bandwidth-delay tradeoff is provided., Comment: conference version appeared at Globecom 2008

In this paper, pilot-assisted transmission over time-selective flat fading channels is studied. It is assumed that noncausal and causal Wiener filters are employed at the receiver to perform channel estimation with the aid of training symbols sent periodically by the transmitter. For both filters, the variances of estimate errors are obtained from the Doppler power spectrum of the channel. Subsequently, achievable rate expressions are provided. The training period, and data and training power allocations are jointly optimized by maximizing the achievable rate expressions. Numerical results are obtained by modeling the fading as a Gauss-Markov process. The achievable rates of causal and noncausal filtering approaches are compared. For the particular ranges of parameters considered in the paper, the performance loss incurred by using a causal filter as opposed to a noncausal filter is shown to be small. The impact of aliasing that occurs in the undersampled version of the channel Doppler spectrum due to fast fading is analyzed. Finally, energy-per-bit requirements are investigated in the presence of noncausal and causal Wiener filters., Comment: appeared at IEEE SPAWC 2008

In this paper, communication over imperfectly-known fading channels with different degrees of cooperation is studied. The three-node relay channel is considered. It is assumed that communication starts with the network training phase in which the receivers estimate the fading coefficients of their respective channels. In the data transmission phase, amplify-and-forward and decode-and-forward relaying schemes are employed. For different cooperation protocols, achievable rate expressions are obtained. These achievable rate expressions are then used to find the optimal resource allocation strategies. In particular, the fraction of total time or bandwidth that needs to be allocated to the relay for best performance is identified. Under a total power constraint, optimal allocation of power between the source and relay is investigated. Finally, bit energy requirements in the low-power regime are studied., Comment: appeared at IEEE SPAWC 2008

In this paper, transmission over time-selective, flat fading relay channels is studied. It is assumed that channel fading coefficients are not known a priori. Transmission takes place in two phases: network training phase and data transmission phase. In the training phase, pilot symbols are sent and the receivers employ single-pilot MMSE estimation or noncausal Wiener filter to learn the channel. Amplify-and-Forward (AF) and Decode-and-Forward (DF) techniques are considered in the data transmission phase and achievable rate expressions are obtained. The training period, and data and training power allocations are jointly optimized by using the achievable rate expressions. Numerical results are obtained considering Gauss-Markov and lowpass fading models. Achievable rates are computed and energy-per-bit requirements are investigated. The optimal power distributions among pilot and data symbols are provided., Comment: appeared at CISS 2008

In this paper, achievable rates and optimal resource allocation strategies for imperfectly-known fading relay channels are studied. It is assumed that communication starts with the network training phase in which the receivers estimate the fading coefficients of their respective channels. In the data transmission phase, amplify-and-forward and decode-and-forward relaying schemes with different degrees of cooperation are considered, and the corresponding achievable rate expressions are obtained. Three resource allocation problems are addressed: 1) power allocation between data and training symbols; 2) time/bandwidth allocation to the relay; 3) power allocation between the source and relay in the presence of total power constraints. The achievable rate expressions are employed to identify the optimal resource allocation strategies. Finally, energy efficiency is investigated by studying the bit energy requirements in the low-SNR regime.

The central design challenge in next generation wireless systems is to have these systems operate at high bandwidths and provide high data rates while being cognizant of the energy consumption levels especially in mobile applications. Since communicating at very high data rates prohibits obtaining high bit resolutions from the analog-to-digital (A/D) converters, analysis of the energy efficiency under the assumption of hard-decision detection is called for to accurately predict the performance levels. In this paper, transmission over the additive white Gaussian noise (AWGN) channel, and coherent and noncoherent fading channels is considered, and the impact of hard-decision detection on the energy efficiency of phase and frequency modulations is investigated. Energy efficiency is analyzed by studying the capacity of these modulation schemes and the energy required to send one bit of information reliably in the low signal-to-noise ratio (SNR) regime. The capacity of hard-decision-detected phase and frequency modulations is characterized at low SNR levels through closed-form expressions for the first and second derivatives of the capacity at zero SNR. Subsequently, bit energy requirements in the low-SNR regime are identified. The increases in the bit energy incurred by hard-decision detection and channel fading are quantified. Moreover, practical design guidelines for the selection of the constellation size are drawn from the analysis of the spectral efficiency--bit energy tradeoff., Comment: To appear in the IEEE Transactions on Wireless Communications

In this paper, the capacity and energy efficiency of training-based communication schemes employed for transmission over a-priori unknown Rayleigh block fading channels are studied. In these schemes, periodically transmitted training symbols are used at the receiver to obtain the minimum mean-square-error (MMSE) estimate of the channel fading coefficients. Initially, the case in which the product of the estimate error and transmitted signal is assumed to be Gaussian noise is considered. In this case, it is shown that bit energy requirements grow without bound as the signal-to-noise ratio (SNR) goes to zero, and the minimum bit energy is achieved at a nonzero SNR value below which one should not operate. The effect of the block length on both the minimum bit energy and the SNR value at which the minimum is achieved is investigated. Flash training and transmission schemes are analyzed and shown to improve the energy efficiency in the low-SNR regime. In the second part of the paper, the capacity and energy efficiency of training-based schemes are investigated when the channel input is subject to peak power constraints. The capacity-achieving input structure is characterized and the magnitude distribution of the optimal input is shown to be discrete with a finite number of mass points. The capacity, bit energy requirements, and optimal resource allocation strategies are obtained through numerical analysis. The bit energy is again shown to grow without bound as SNR decreases to zero due to the presence of peakedness constraints. The improvements in energy efficiency when on-off keying with fixed peak power and vanishing duty cycle is employed are studied. Comparisons of the performances of training-based and noncoherent transmission schemes are provided.

In this paper, the performance of signaling strategies with high peak-to-average power ratio is analyzed over both coherent and noncoherent fading channels. Two modulation schemes, namely on-off phase-shift keying (OOPSK) and on-off frequency-shift keying (OOFSK), are considered. Initially, uncoded systems are analyzed. For OOPSK and OOFSK, the optimal detector structures are identified and analytical expressions for the error probabilities are obtained for arbitrary constellation sizes. Numerical techniques are employed to compute the error probabilities. It is concluded that increasing the peakedness of the signals results in reduced error rates for a given power level and hence equivalently improves the energy efficiency for fixed error probabilities. The coded performance is also studied by analyzing the random coding error exponents achieved by OOPSK and OOFSK signaling.

In this paper, achievable rates of imperfectly-known fading relay channels are studied. It is assumed that communication starts with the network training phase in which the receivers estimate the fading coefficients of their respective channels. In the data transmission phase, amplify-and-forward and decode-and-forward relaying schemes are considered, and the corresponding achievable rate expressions are obtained. The achievable rate expressions are then employed to identify the optimal resource allocation strategies.

In this paper, the performance of signaling strategies with high peak-to-average power ratio is analyzed in both coherent and noncoherent fading channels. Two recently proposed modulation schemes, namely on-off binary phase-shift keying and on-off quaternary phase-shift keying, are considered. For these modulation formats, the optimal decision rules used at the detector are identified and analytical expressions for the error probabilities are obtained. Numerical techniques are employed to compute the error probabilities. It is concluded that increasing the peakedness of the signals results in reduced error rates for a given power level and hence improve the energy efficiency., Comment: Proc. of the 40th Annual Asilomar Conference on Signals, Systems, and Computers, 2006

In this paper, the error performance of on-off frequency shift keying (OOFSK) modulation over fading channels is analyzed when the receiver is equipped with multiple antennas. The analysis is conducted in two cases: the coherent scenario where the fading is perfectly known at the receiver, and the noncoherent scenario where neither the receiver nor the transmitter knows the fading coefficients. For both cases, the maximum a posteriori probability (MAP) detection rule is derived and analytical probability of error expressions are obtained. The effect of fading correlation among the receiver antennas is also studied. Simulation results indicate that for sufficiently low duty cycle values, lower probability of error values with respect to FSK signaling are achieved. Equivalently, when compared to FSK modulation, OOFSK with low duty cycle requires less energy to achieve the same probability of error, which renders this modulation a more energy efficient transmission technique., Comment: Proc. of the 2007 IEEE Wireless Communications and Networking Conference