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This paper focuses on the design and evaluation of pragmatic schemes for delay-sensitive communication. Specifically, this contribution studies the operation of data links that employ incremental redundancy as a means to shield information bits from the degradation associated with unreliable channels. While this inquiry puts forth a general methodology, exposition centers around erasure channels because they are well suited for analysis. Nevertheless, the goal is to identify both structural properties and design guidelines that are broadly applicable. Conceptually, this paper leverages a methodology, termed sequential differential optimization, aimed at identifying near-optimal block sizes for hybrid ARQ. This technique is applied to erasure channels and it is extended to scenarios where throughput is maximized subject to a constraint on the feedback rate. The analysis shows that the impact of the coding strategy adopted and the propensity of the channel to erase symbols naturally decouple when maximizing throughput. Ultimately, block size selection is informed by approximate distributions on the probability of decoding success at every stage of the incremental transmission process. This novel perspective, which rigorously bridges hybrid automatic repeat request and coding, offers a computationally efficient framework to select code rates and blocklengths for incremental redundancy. These findings are supported through numerical results. [ABSTRACT FROM AUTHOR]

To realize high energy-efficient, high spectrum-efficient, and high-throughput data transmission, a multi-carrier differential chaos shift keying communication system with hybrid index modulation, referred to as HIM-MC-DCSK system, is proposed in this paper. In the HIM-MC-DCSK system, we intelligently integrate the carrier-number-index technique and carrier-index technique into the MC-DCSK modulation in order to significantly boost the transmission efficiency in wireless communication systems. Especially, we use a pair of orthogonal signals to represent the active and inactive subcarriers in the HIM-MC-DCSK system so as to exploit all the subcarriers to transmit information bits. In addition, the theoretical bit-error-rate (BER) expressions of the HIM-MC-DCSK system are derived over additive white Gaussian noise (AWGN) and multipath Rayleigh fading channels. Also, the data rate, spectrum efficiency, energy efficiency, and complexity of the proposed system are carefully analyzed. Monte-Carlo simulations not only verify the accuracy of the theoretical analysis but also illustrate the superiority of the proposed system. [ABSTRACT FROM AUTHOR]

Inverse, or negative binomial, sampling is often used when the observation of interest occurs extremely infrequently. As this is the case in bit error rate (BER) simulations, especially in high signal-to-noise ratio cases, negative binomial sampling can be advantageously employed in a computationally economic fashion to compare bit error rates between different systems. When the results of two negative binomial sampling tests are compared, point estimates and interval estimates quantify the performance relationship between the results of the tests. This paper derives a new, optimal, logarithmically symmetric confidence interval estimator for the ratio of BER estimates derived from two negative binomial tests. In addition, a three-sided hypothesis test with a single significance level is derived to quantify the confidence of the relationship between the two systems. Low-BER approximations for the confidence interval and decision thresholds are derived based on the F-distribution. The approximation is shown to work with BERs as high as 10^-2. An example inspired by bit interleaved coded modulation shows how the technique can be used to reduce simulation time by an order of magnitude and facilitate straightforward interpretation and comparison between different systems. Negative binomial sampling is recommended for comparison experiments where BER is the key metric. [ABSTRACT FROM PUBLISHER]

Channel estimation is challenging for the reconfigurable intelligent surface (RIS)-aided wireless communications. Since the number of coefficients of the cascaded channel among the base station (BS), the RIS, and the user equipment (UE), is the product of the number of BS antennas, the number of RIS elements, and the number of UEs, the pilot overhead can be prohibitively high. In this paper, we propose a two-timescale channel estimation framework to exploit the property that the BS-RIS channel is high-dimensional but quasi-static, while the RIS-UE channel is mobile but low-dimensional. Specifically, to estimate the quasi-static BS-RIS channel, we propose a dual-link pilot transmission scheme, where the BS transmits downlink pilots and receives uplink pilots reflected by the RIS. Then, we propose a coordinate descent-based algorithm to recover the BS-RIS channel. Since the quasi-static BS-RIS channel is estimated less frequently than the mobile channel is, the average pilot overhead can be reduced from a long-term perspective. Although the mobile RIS-UE channel has to be frequently estimated in a small timescale, the associated pilot overhead is low thanks to its low dimension. Simulation results show that the proposed two-timescale channel estimation framework can achieve accurate channel estimation with low pilot overhead. [ABSTRACT FROM AUTHOR]

Recently, mutually orthogonal complementary sequence sets (MOCSSs) have been found many important applications in communication systems, radar, etc. Most of the known constructions of MOCSSs are based on generalized Boolean functions (GBFs) and hence mostly have lengths of power-of-two. A few constructions of MOCSSs are also based on paraunitary (PU) matrices and hence mostly have power-of-an-integer lengths. The objective of this paper is to develop a general framework to construct more MOCSSs consisting of sequences with non-power-of-two lengths. The proposed framework is based on complete complementary codes and even-shift complementary sequence sets. [ABSTRACT FROM AUTHOR]

In conventional hybrid beamforming approaches, the number of radio-frequency (RF) chains is the bottleneck on the achievable spatial multiplexing gain. Recent studies have overcome this limitation by increasing the update-rate of the RF beamformer. This paper presents a framework to design and evaluate such approaches, which we refer to as agile RF beamforming, from theoretical and practical points of view. In this context, we consider the impact of the number of RF-chains, phase shifters’ speed, and resolution to design agile RF beamformers. Our analysis and simulations indicate that even an RF-chain-free transmitter, which its beamformer has no RF-chains, can provide a promising performance compared with fully-digital systems and significantly outperform the conventional hybrid beamformers. Then, we show that the phase shifter’s limited switching speed can result in signal aliasing, in-band distortion, and out-of-band emissions. We introduce performance metrics and approaches to measure such effects and compare the performance of the proposed agile beamformers using the Gram-Schmidt orthogonalization process. Although this paper aims to present a generic framework for deploying agile RF beamformers, it also presents extensive performance evaluations in communication systems in terms of adjacent channel leakage ratio, sum-rate, power efficiency, error vector magnitude, and bit-error rates. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the resource allocation algorithm design for multicarrier solar-powered unmanned aerial vehicle (UAV) communication systems. In particular, the UAV is powered by the solar energy enabling sustainable communication services to multiple ground users. We study the joint design of the 3D aerial trajectory and the wireless resource allocation for maximization of the system sum throughput over a given time period. As a performance benchmark, we first consider an off-line resource allocation design assuming non-causal knowledge of the channel gains. The algorithm design is formulated as a mixed-integer non-convex optimization problem taking into account the aerodynamic power consumption, solar energy harvesting, a finite energy storage capacity, and the quality-of-service requirements of the users. Despite the non-convexity of the optimization problem, we solve it optimally by applying monotonic optimization to obtain the optimal 3D-trajectory and the optimal power and subcarrier allocation policy. Subsequently, we focus on the online algorithm design that only requires real-time and statistical knowledge of the channel gains. The optimal online resource allocation algorithm is motivated by the off-line scheme and entails a high computational complexity. Hence, we also propose a low-complexity iterative suboptimal online scheme based on the successive convex approximation. Our simulation results reveal that both the proposed online schemes closely approach the performance of the benchmark off-line scheme and substantially outperform two baseline schemes. Furthermore, our results unveil the tradeoff between solar energy harvesting and power-efficient communication. In particular, the solar-powered UAV first climbs up to a high altitude to harvest a sufficient amount of solar energy and then descends again to a lower altitude to reduce the path loss of the communication links to the users it serves. [ABSTRACT FROM AUTHOR]

The identification of maximum tolerable levels for potential mismatches is critical when designing communication systems. In this paper, we derive maximum tolerable levels for time-interleaved analog-to-digital-converter (TI-ADC) gain mismatch in orthogonal frequency-division multiplexing (OFDM) systems. To this end, we first analytically evaluate the bit error rate (BER) for square quadrature amplitude modulated-OFDM systems that are impaired by: 1) the gain mismatch of a TI-ADC and 2) the channel estimation errors (CEEs) of a zero-forcing equalizer. Our analysis includes the cases of a frequency-selective Rayleigh fading channel and a wired channel. Next, built on the obtained BER expressions, a threshold is established on the gain mismatch level, at which an error floor caused by the gain mismatch is below a given BER value at high signal-to-noise ratios in the absence of CEEs. Finally, numerical results further show that if and only if we set the gain mismatch level below 0.25 of this threshold, there is essentially no BER performance degradation compared with the mismatch-free case. [ABSTRACT FROM AUTHOR]

In this paper, we study a quantized feedback scheme to maximize the goodput of a finite blocklength communication scenario over a quasi-static fading channel. It is assumed that the receiver has perfect channel state information (CSI) and sends back the CSI to the transmitter over a resolution-limited error-free feedback channel. With this partial CSI, the transmitter is supposed to select the optimum transmission rate, such that it maximizes the overall goodput of the communication system. This problem has been studied for the asymptotic blocklength regime, however, no solution has so far been presented for finite blocklength. Here, we study this problem in two cases: with and without constraint on reliability. We first formulate the optimization problems and analytically solve them. Iterative algorithms that successfully exploit the system parameters for both cases are presented. It is shown that although the achievable maximum goodput decreases with shorter blocklengths and higher reliability requirements, significant improvement can be achieved even with coarsely quantized feedback schemes. [ABSTRACT FROM AUTHOR]

Channel estimation is one of the main challenges for implementing reconfigurable intelligent surface (RIS)-aided communication system with a large number of antennas at the base station (BS) because RIS is equipped with many passive reflective elements without active transmitting/receiving and signal processing abilities. In this paper, we focus on the channel estimation in a general RIS-aided multi-user mmWave communication system. Specifically, a novel two-phase channel estimation scheme consisting of on-line and off-line phases is proposed to estimate the BS-RIS channel, RIS-user channel, and BS-user channel, respectively. Inspired by the characteristics of few scatterers in mmWave communication systems, the antenna domain channels are converted into the virtual angular domain channels by using the discrete Fourier transform (DFT) matrix. Thus, the estimation problem can be formulated as a compressed sensing (CS) problem, and solved by using efficient vector approximate message passing (VAMP) algorithm with expectation-maximization (EM) to learn unknown parameters and obtain the estimates simultaneously. Simulation results show that, the above algorithm with two choices of prior distributions in the proposed mmWave RIS-aided multi-user system has fast convergence speed and desirable estimation performance. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel communication framework, Acoustic-WiFi, that utilizes the acoustic channel (i.e., microphone/speaker) as a control channel to develop more efficient Wi-Fi networks. We used the Acoustic-WiFi framework to develop a Power Saving Mode (PSM) scheme; A2PSM, and a smart contention resolution scheme; Harmony. In A2PSM, we propose an acoustic channel assisted power saving scheme for the Wi-Fi interface, which addresses the inefficiency of the existing power saving schemes in smart devices. In this scheme, we leverage the low power consumption of the acoustic interfaces to reduce the wakeup events of the Wi-Fi interface when it is in power saving mode. We develop a small-scale prototype testbed on real smartphones to evaluate the proposed A2PSM scheme. Experiments show that A2PSM could save up to more than 25% more power than the existing schemes. In Harmony, we address the overhead of the Wi-Fi backoff scheme (i.e., contention window countdown, DIFS) and reduce the overall collisions among the devices. Harmony uses the acoustic channel for contention resolution in Wi-Fi networks. We also evaluate Harmony using real testbed and simulation. Experiments using the testbed show a 40% gain in throughput over the 802.11 Wi-Fi backoff scheme, while simulation results show a gain of more than 27% for dense networks. [ABSTRACT FROM AUTHOR]

This paper proposes a novel deep learning-based error correction coding scheme for AWGN channels under the constraint of one-bit quantization in receivers. Specifically, it is first shown that the optimum error correction code that minimizes the probability of bit error can be obtained by perfectly training a special autoencoder, in which “perfectly” refers to converging the global minima. However, perfect training is not possible in most cases. To approach the performance of a perfectly trained autoencoder with a suboptimum training, we propose utilizing turbo codes as an implicit regularization, i.e., using a concatenation of a turbo code and an autoencoder. It is empirically shown that this design gives nearly the same performance as to the hypothetically perfectly trained autoencoder, and we also provide a theoretical proof of why that is so. The proposed coding method is as bandwidth efficient as the integrated (outer) turbo code, since the autoencoder exploits the excess bandwidth from pulse shaping and packs signals more intelligently thanks to sparsity in neural networks. Our results show that the proposed coding scheme at finite block lengths outperforms conventional turbo codes even for QPSK modulation. Furthermore, the proposed coding method can make one-bit quantization operational even for 16-QAM. [ABSTRACT FROM AUTHOR]

In this paper, we investigate robust resource allocation algorithm design for multiuser downlink multiple-input single-output (MISO) unmanned aerial vehicle (UAV) communication systems, where we account for the various uncertainties that are unavoidable in such systems and, if left unattended, may severely degrade system performance. We jointly optimize the two-dimensional (2-D) trajectory and the transmit beamforming vector of the UAV for minimization of the total power consumption. The algorithm design is formulated as a non-convex optimization problem taking into account the imperfect knowledge of the angle of departure (AoD) caused by UAV jittering, user location uncertainty, wind speed uncertainty, and polygonal no-fly zones (NFZs). Despite the non-convexity of the optimization problem, we solve it optimally by employing monotonic optimization theory and semidefinite programming relaxation which yields the optimal 2-D trajectory and beamforming policy. Since the developed optimal resource allocation algorithm entails a high computational complexity, we also propose a suboptimal iterative low-complexity scheme based on successive convex approximation to strike a balance between optimality and computational complexity. Our simulation results reveal not only the significant power savings enabled by the proposed algorithms compared to two baseline schemes, but also confirm their robustness with respect to UAV jittering, wind speed uncertainty, and user location uncertainty. Moreover, our results unveil that the joint presence of wind speed uncertainty and NFZs has a considerable impact on the UAV trajectory. Nevertheless, by counteracting the wind speed uncertainty with the proposed robust design, we can simultaneously minimize the total UAV power consumption and ensure a secure trajectory that does not trespass any NFZ. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) has emerged as an important transmission technology for numerous applications in Internet of Things (IoT) systems. Thus, in this paper, we investigate the application of RIS in energy harvesting (EH) based unmanned aerial vehicle (UAV) communication network with finite block length (BL) codes, where a rotary wing type flying UAV communicates with the multiple single antenna IoT users with the aid of multiple RISs mounted on several skyscraper buildings. To transmit the signal to a particular IoT user, the UAV selects an RIS on the basis of either UAV-RIS (i.e., partial) or UAV-RIS-IoT (i.e., full) channel state information (CSI) and then transmits the signal through the selected RIS along with the direct link transmission. In particular, we derive (i) the expression for probability of RIS selection, (ii) the statistical distribution of instantaneously received information signal-to-noise ratio (SNR) at the IoT user. Based on the derived statistics, we analyze the performance of the considered system under finite BL codes in terms of the average outage probability, average block error rate (ABLER) and goodput averaged over entire flying duration. Moreover, the BLER performance with finite BL codes is also compared with the infinite BL codes scenario. Additionally, we also investigate the impact of various channel and system parameters like imperfect CSI, number of RISs and the number of reflecting elements at each RIS, location of IoT users, variable altitude of the UAV, and the severity of channel fading of UAV-RIS link on the system performance. Furthermore, we have obtained the optimum UAV location in each time slot which minimizes the ABLER per time slot over all the users in the network. The analytical results are corroborated with Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the performance of an RIS-aided wireless communication system subject to outdated channel state information that may operate in both the near- and far-field regions. In particular, we take two RIS deployment strategies into consideration: (i) the centralized deployment, where all the reflecting elements are installed on a single RIS and (ii) the distributed deployment, where the same number of reflecting elements are placed on multiple RISs. For both deployment strategies, we derive accurate closed-form approximations for the ergodic capacity, and we introduce tight upper and lower bounds for the ergodic capacity to obtain useful design insights. From this analysis, we unveil that an increase of the transmit power, the Rician- $K$ factor, the accuracy of the channel state information and the number of reflecting elements help improve the system performance. Moreover, we prove that the centralized RIS-aided deployment may achieve a higher ergodic capacity as compared with the distributed RIS-aided deployment when the RIS is located near the base station or near the user. In different setups, on the other hand, we prove that the distributed deployment outperforms the centralized deployment. Finally, the analytical results are verified by using Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

Hardware impairments in general and amplifier nonlinearity in particular severely limit the performance of communication links. This paper analytically provides statistical results on how a nonlinear amplifier affects the quality of signals in communication systems. In particular, we propose a statistical model that describes the nonlinear distortion as a function of the input signal’s average and instantaneous power and captures the pulse-shaping and matched filters’ effects. We show through simulations and complementary measurements that the proposed model can provide an authentic connection between the communication system parameters, power amplifier nonlinearity characteristics, and the communication system performance. It serves not only as a reliable model for nonlinear distortion analysis but also as a design tool that allows optimization of signal and filter characteristics with respect to nonlinear distortion. [ABSTRACT FROM AUTHOR]

This paper investigates power allocation for minimizing the average bit error probability (BEP) in hybrid communication systems, more specifically hybrid power line/wireless systems (HPWSs). In this regard, a brief discussion of HPWSs is presented in order to point out the complementary characteristics of power line and wireless media. By considering orthogonal frequency-division multiplexing and maximal-ratio combining, optimization problems associated with the minimization of the average BEP in hybrid communication systems are formulated under two distinct transmission power constraints, called sum power and sum power-channel constraints. For both constraints, it is demonstrated that at most one medium should be used for data transmission over subchannels with the same index in order to minimize the average BEP in hybrid communication systems. Based on this finding, power allocation algorithms are derived for this purpose in HPWSs. Numerical analyses are then used to validate the proposed algorithms by comparing them with interior-point-based power allocation algorithms. In addition, performance comparisons show the advantage of the proposals over alternative algorithms from the literature, including previous algorithms proposed for maximizing the achievable data rate. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) stands out as a promising technology by enhancing the electromagnetic wave propagation environment with its passive reflecting elements. In this paper, we focus on the ergodic sum-rate analysis and maximization of the RIS-assisted uplink multiuser multiple-input multiple-output (MIMO) multiple-access channel (MAC) under Rician fading by exploiting full statistical channel state information (CSI). The spatial correlations at the base station, the users, and the RIS are also considered. By using the replica method originated in statistical physics, the closed-form asymptotic ergodic sum-rate of the system is first derived in the large-system regime on the account of the unique channel structure of the RIS-assisted MIMO-MAC system. Then, based on the derived asymptotic ergodic sum-rate, we propose an alternating optimization (AO) algorithm to jointly design the transmit covariance matrix of users and the phase-shifting matrix of RIS with full statistical CSI. Simulation results are also demonstrated to verify the accuracy of the derived asymptotic ergodic sum-rate and the superiority of the proposed AO algorithm. The results reveal that the derived closed-form asymptotic ergodic sum-rate matches very well with the Monte Carlo results even for a small number of antennas, and the proposed AO algorithm can achieve up to 10 bps/Hz gain at high signal-to-noise (SNR) regime, which is therefore valuable for future RIS-assisted MIMO-MAC system designs. [ABSTRACT FROM AUTHOR]

Free space optical (FSO) channel provides a significantly large transmission capacity. However, in the presence of random jamming attacks, the efficacy of FSO communication channel can be affected critically. In this paper, the discrete-input continuous-output memoryless channel (DCMC) capacity of a single-input single-output FSO communication system is investigated under the random jamming effects. The ergodic channel capacity analysis is performed over additive non-Gaussian noise channel (jamming noise channel). The derived closed-form expression of DCMC capacity for the considered FSO system and also, the effects of partial-band jamming and broadband jamming over the FSO channel capacity are verified through simulation results. It is observed that the FSO channel capacity is very sensitive to the degree of jamming and the ergodic channel capacity alters crucially even for small change in jamming probability. The derived results are utilized to study the considered network in the presence of a rational jammer whose ability to jam is limited by its battery capacity. The presence of a rational jammer is addressed by modelling the interaction between the FSO transmitter and the jammer as a non-cooperative game. The closed-form expressions of the equilibrium of the proposed game are derived and verified through simulation. The game-theoretic solution provides a performance improvement of 74% in comparison to uniform power allocation. [ABSTRACT FROM AUTHOR]

This paper concerns the construction and hardware execution of (n, n(n-1), n-1) permutation group codes (PGCs) for communication systems. Cyclic shift techniques acting on a permutation, including cyclic shift operators and their compound functions (CFs), are defined and demonstrated, then compared to other tools such as cyclic subgroups and n-dimension cyclic shift registers. A generalized finite state machine is established that can enumerate n! permutations based on complete CFs. This is a hardware-oriented algorithm that is capable of being significantly faster than all existing algorithms which we can find up to now. After this, the ideal structural features for an ordered set of n! permutations are discussed and the multiset features of (n, n(n-1), n-1)-PGCs in this ordered set are pinpointed. A simpler way of generating (n, n(n-1), n-1)-PGCs is then developed using cyclic shift techniques, where the code length n is a prime. This outperforms existing approaches using composite operation and affine transform on module-n operation. The simulation experiments in AWGN channel show that the performance on codeword error rates (WER) and signal-noise ratio (SNR) becomes better as the code length increases and the best SNR performance achieves −0.8 dB at 10−5 WER for code length n=11. [ABSTRACT FROM AUTHOR]

In this paper, we study the effects of subjective biases on strategic information transmission (SIT) within a Stackelberg game setting, where a human transmitter (leader) communicates an encoded source message to a human receiver (follower) so that the receiver decodes back a desired version of the original source signal. We model human decisions using Rieger–Wang’s prospect theory, which is an extension of traditional prospect theory to continuous decision spaces. Having found a closed-form expression for the receiver’s best response strategy under any general setting, we consider two settings: Gaussian SIT games and exponential SIT games. While the Gaussian SIT games result in strategies that are independent of subjective biases of both the transmitter and the receiver, we show that the equilibrium strategies in exponential SIT games depend on the subjective biases of both the transmitter and the receiver. Numerical results are presented to illustrate results in both Gaussian and exponential settings. [ABSTRACT FROM AUTHOR]

Increasing demands for spectrum have necessitated the coexistence of communications and radar systems within the same band. This paper investigates how an unaltered radar system affects the performance of a communications receiver. For a single-carrier communications system, it is shown that a low power radar signal can be treated as Gaussian noise while a strong radar signal can be subtracted off the received signal, but in doing so one of the two signal dimensions is lost. Complex-valued constellation design problems are next proposed, with the goal of either minimizing the error rate under a power constraint, or maximizing the transmission rate under both error rate and power constraints. Numerically, the designed constellation is shaped as a concentric hexagon for weak radar interference while it morphs into an uneven pulse amplitude modulation for strong interference. A multi-carrier orthogonal frequency division multiplexing communications system is lastly considered. Due to the radar interference, the received signal becomes correlated over time and across carriers. To reduce the complexity of the optimal receiver, several suboptimal decoders are analyzed, among which the one that discards the correlations between subcarriers is numerically found to perform close to the optimal one. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS), a recently introduced technology for future wireless communication systems, enhances the spectral and energy efficiency by intelligently adjusting the propagation conditions between base stations (BSs) and mobile equipments (MEs). An RIS consists of many low-cost passive reflecting elements that are optimized to improve the quality of the received signal. In this paper, we study the problem of power control at the BS and RIS optimization for application to physical-layer broadcasting. Our goal is to minimize the transmit power at the BS by jointly designing the transmit beamforming at the BS and the phase shifts of the passive elements at the RIS. Furthermore, to help validate the proposed optimization methods, we derive lower bounds to quantify the average transmit power at the BS as a function of the number of MEs, the number of RIS elements, and the number of antennas at the BS. The simulation results demonstrate that the average transmit power at the BS is close to the lower bound in an RIS-aided system, and is significantly lower than the average transmit power in conventional schemes without an RIS. [ABSTRACT FROM AUTHOR]

Contemporary wireless networks are tasked with supporting different connection profiles, including real-time traffic and delay-sensitive communications. This creates a need to better understand the fundamental limits of forward error correction in non-asymptotic regimes. This paper characterizes the performance of block codes over finite-state channels and evaluates their queueing performance under maximum-likelihood decoding. Classical results from digital communications are revisited in the context of channels with rare transitions, and bounds on the probabilities of decoding failure are derived for random codes. This creates an analysis framework where channel dependencies within and across codewords are preserved. These results are subsequently integrated into a queueing problem formulation. [ABSTRACT FROM PUBLISHER]

Determining the capacity of a modulation scheme is a fundamental topic of interest. Index modulations (IM), such as spatial modulation (SMod), polarized modulation (PMod), or frequency index modulation (FMod), are widely studied in the literature. However, finding a closed-form analytical expression for their capacity still remains an open topic. In this paper, we formulate closed-form expressions for the instantaneous capacity of IM, together with its second- and fourth-order approximations. We show that, in average, the second-approximation error tends to zero for low signal to noise ratio (SNR) and is o\left (\textrm SNR\right ) . Also, a detailed analysis of the ergodic capacity over Rayleigh, Rice, and Nakagami- $m$ channel distributions is provided. As application of the capacity analysis, we leverage the proposed expressions to compute the ergodic capacities of SMod for different antenna configuration and correlations, PMod for different channel components and conditions, and FMod for different frequency separations. [ABSTRACT FROM PUBLISHER]

This paper proposes an improved receiver for the Tomlinson-Harashima precoder (THP). In this paper we demonstrate that most of the capacity loss associated with conventional THP is due to the suboptimal receiver, which is a simple modulo operation. We then demonstrate how this loss can can be avoided with the optimization of the receiver. In the suboptimal receiver the modulo operation ignores the dependency between the implicitly added sequence of symbols removed by it. We then implement a THP with quantized outputs. The quantized outputs enable to implement a Maximum A-Posteriori Probability (MAP) receiver that exploits the dependency between the received symbols. The MAP receiver is named Enhanced MODulo operation (EMOD), and operates as an inner decoder within an iterative scheme, either with outer Low Density Parity Check (LDPC) code or outer Turbo Code. Simulation results show considerable gains relative to coded conventional THP, and also relative to the Turbo-Equalizer (TE) (which does not use a precoder in the transmitter). [ABSTRACT FROM AUTHOR]

Fuel-powered UAVs have long endurance of flight, heavy payload and adaptation to extreme environment. The mechanical operation and communication power are supported independently by fuel and batteries. In the paper, we study the energy efficiency of the communication system with a fuel-powered UAV relay. We consider a three-node communication network, consisting of a mobile relay, a source node, and a destination node. The UAV relay is able to change its 3-D trajectory to maintain high probability of LoS channels, receiving information from the fixed source node and transmitting it to the fixed destination node. The power allocation scheme and UAV’s trajectory are designed to maximize the system energy efficiency, considering the constraints of speeds, UAV’s altitudes, communication and mechanical energy consumption, the required data rates of the destination node and information-causality. We solve the power allocation sub-problem by splitting the domain of variables and transforming it into a convex optimization problem. And then a suboptimal scheme is provided to design the trajectory based on successive convex approximation method. Numerical results show the convergence of the proposed schemes and the performance of the proposed algorithms. The influences of time slots, constraints of fuel, communication power and required data rates are discussed. [ABSTRACT FROM AUTHOR]

In this paper, we aim to obtain the optimal tradeoff between the average delay and the average power consumption in a communication system. In our system, the arrivals occur at each timeslot according to a Bernoulli arrival process, and are buffered at the transmitter waiting to be scheduled. We consider a finite buffer and allow the scheduling decision to depend on the buffer occupancy. In order to capture the realism in communication systems, the transmission power is assumed to be an increasing and convex function of the number of packets transmitted in each timeslot. This problem is modeled as a constrained Markov decision process (CMDP). We first prove that the optimal policy of the Lagrangian relaxation of the CMDP is deterministic and threshold-based. We then show that the optimal delay-power tradeoff curve is convex and piecewise linear, and the optimal policies of the original problem are also threshold-based. Based on the results, we propose an algorithm to obtain the optimal policy and the optimal tradeoff curve. We also show that the proposed algorithm is much more efficient than using general methods. The theoretical results and the algorithm are validated by linear programming and simulations. [ABSTRACT FROM PUBLISHER]

We consider the channel access problem arising in opportunistic scheduling over fading channels, cognitive radio networks, and server scheduling. The multi-channel communication system consists of $N$ channels. Each channel evolves as a time-nonhomogeneous multi-state Markov process. At each time instant, a user chooses $M$ channels to transmit information, and obtains some reward, i.e., throughput, based on the states of the chosen channels. The objective is to design an access policy, i.e., which channels should be accessed at each time instant, such that the expected accumulated discounted reward is maximised over a finite or infinite horizon. The considered problem can be cast into a restless multi-armed bandit (RMAB) problem, which is PSPACE-hard, with the optimal policy usually intractable due to the exponential computation complexity. Hence, a natural alternative is to consider the easily implementable myopic policy that only maximises the immediate reward but ignores the impact of the current strategy on the future reward. In this paper, we perform an analytical study on the performance of the myopic policy for the considered RMAB problem, and establish a set of closed-form conditions to guarantee the optimality of the myopic policy. [ABSTRACT FROM PUBLISHER]

A new Multi-Carrier Differential Chaos Shift Keying (MC-DCSK) modulation is presented in this paper. The system endeavors to provide a good trade-off between robustness, energy efficiency and high data rate, while still being simple compared to conventional multi-carrier spread spectrum systems. This system can be seen as a parallel extension of the DCSK modulation where one chaotic reference sequence is transmitted over a predefined subcarrier frequency. Multiple modulated data streams are transmitted over the remaining subcarriers. This transmitter structure increases the spectral efficiency of the conventional DCSK system and uses less energy. The receiver design makes this system easy to implement where no radio frequency (RF) delay circuit is needed to demodulate received data. Various system design parameters are discussed throughout the paper, including the number of subcarriers, the spreading factor, and the transmitted energy. Once the design is explained, the bit error rate performance of the MC-DCSK system is computed and compared to the conventional DCSK system under multipath Rayleigh fading and an additive white Gaussian noise (AWGN) channels. Simulation results confirm the advantages of this new hybrid design. [ABSTRACT FROM AUTHOR]

In this paper, we study the trajectory and resource allocation design for downlink energy-efficient secure unmanned aerial vehicle (UAV) communication systems, where an information UAV assisted by a multi-antenna jammer UAV serves multiple ground users in the existence of multiple ground eavesdroppers. The resource allocation strategy and the trajectory of the information UAV, and the jamming policy of the jammer UAV are jointly optimized for maximizing the system energy efficiency. The joint design is formulated as a non-convex optimization problem taking into account the quality of service (QoS) requirement, the security constraint, and the imperfect channel state information (CSI) of the eavesdroppers. The formulated problem is generally intractable. As a compromise approach, the problem is divided into two subproblems which facilitates the design of a low-complexity suboptimal algorithm based on alternating optimization approach. Simulation results illustrate that the proposed algorithm converges within a small number of iterations and demonstrate some interesting insights: (1) the introduction of a jammer UAV facilitates a highly flexible trajectory design of the information UAV which is critical to improving the system energy efficiency; (2) by exploiting the spatial degrees of freedom brought by the multi-antenna jammer UAV, our proposed design can focus the artificial noise on eavesdroppers offering a strong security mean to the system. [ABSTRACT FROM AUTHOR]

Magnetic Induction (MI) techniques enable efficient wireless communications in dense media with high material absorptions, such as underground soil medium and oil reservoirs. A wide range of novel and important applications in such RF-challenged environments can be realized based on the MI communication mechanism. Despite the potential advantages, the major bottleneck of the MI communication is the limited channel capacity due to the low MI bandwidth. In this paper, the Spread Resonance (RS) strategy is developed for the MI communication in RF-challenged environments which greatly increases the MI channel capacity. Specifically, instead of using the same resonant frequency for all the MI coils, the spread resonance strategy allocates different resonant frequencies for different MI relay and transceiver coils. An optimization solution for the resonant frequency allocation is formulated to maximize the MI channel capacity which captures multiple unique MI effects, including the parasitic capacitor in each MI coil, the Eddy currents in various transmission media with limited conductivities, and the random direction of each coil. Numerical evaluations are provided to validate the significant channel capacity improvements by the proposed SR strategy for MI communication systems. [ABSTRACT FROM AUTHOR]

Considering growing concerns toward green communications, not only their bandwidth efficiency but also their power consumption is expected to gain increasing importance for future communication systems. A power amplifier (PA) is one of the most power consuming analog devices at the transmitter in communication systems and a precise estimation of the power consumption at the transmitter circuit requires the knowledge of its efficiency that depends on the distribution of input signal envelope and the amount of input back-off. In this paper, we develop a simple analytical model that can be used for estimating achievable efficiency of a linear PA as well as the amount of resulting nonlinear distortion for a given modulated signal exclusively from its envelope distribution. Based on this model, the trade-off relationships between the efficiency and signal-to-distortion power ratio for several spectrally efficient linear modulations are examined. It is also shown that in some special cases of Gaussian input and memoryless nonlinearity PA models, the results can be represented in simple closed-form expressions. [ABSTRACT FROM AUTHOR]

This paper presents an enhanced permeable layer mechanism useful for highly robust packetized multimedia transmission. Packet header recovery at various protocol layers using MAP estimation is the cornerstone of the proposed solution. The inherently available intra-layer and inter-layer header correlation proves to be very effective in selecting a reduced set of possible header configurations for further processing. The best candidate is then obtained through soft decoding of CRC protected data and CRC redundancy information itself. Simulation results for WiFi transmission using DBPSK modulated signals over AWGN channels show a substantial (4 to 12 dB) link budget improvement over classical hard decision procedures. We also introduce a sub-optimal and hardware realizable version of the proposed algorithm. [ABSTRACT FROM AUTHOR]

There have been many results on designing transceivers for MIMO channels. In early results, the transceiver is designed for a given bit allocation. In this paper we will jointly design the transceiver and bit allocation for maximizing bit rate. By using a high bit rate assumption, we will see that the optimal transceiver and bit allocation can be obtained in a closed form using simple Hadamard inequality and the Poincaré separation theorem. In the simulation, we will demonstrate the usefulness of the joint design. Simulation results, in which a high bit rate assumption is not used in allocating bits, show that a higher bit rate can be achieved compared to previously reported methods. [ABSTRACT FROM AUTHOR]

In wireless data networks, the optimal routing of data depends on the link capacities which, in turn, are determined by the allocation of communications resources (such as transmit powers and bandwidths) to the links. The optimal performance of the net- work can only be achieved by simultaneous optimization of routing and resource allocation. In this paper, we formulate the simultaneous routing and resource allocation (SRRA) problem, and exploit problem structure to derive efficient solution methods. We use a capacitated multicommodity flow model to describe the data flows in the network. We assume that the capacity of a wireless link is a concave and increasing function of the communications resources allocated to the link, and the communications resources for groups of links are limited. These assumptions allow us to formulate the SRRA problem as a convex optimization problem over the network flow variables and the communications variables. These two sets of variables are coupled only through the link capacity constraints. We exploit this separable structure by dual decomposition. The resulting solution method attains the optimal coordination of data routing in the network layer and resource allocation in the radio control layer via pricing on the link capacities. [ABSTRACT FROM AUTHOR]

We study the problem of lossy joint source-channel coding in a single-user energy harvesting communication system with causal energy arrivals and the energy storage unit may have leakage. In particular, we investigate the achievable distortion in the transmission of a single source via an energy harvesting transmitter over a point-to-point channel. We consider an adaptive joint source-channel coding system, where the length of channel codewords varies based on the available battery charge. We first establish a lower bound on the achievable distortion. Then, as necessary conditions for local optimality, we obtain two coupled equations that determine the mismatch ratio between channel symbols and source symbols as well as the transmission power, both as functions of the battery charge. As examples of continuous and discrete sources, we consider Gaussian and binary sources respectively. For the Gaussian case, we obtain a closed-form expression for the mismatch factor in terms of the $Lambert W$ function, and show that an increasing transmission power policy results in a decreasing mismatch factor policy and vice versa. Finally, we numerically compare the performance of the adaptive mismatch factor scheme to the case of a constant mismatch factor. [ABSTRACT FROM AUTHOR]

In some communication networks, such as passive RFID systems, the energy used to transfer information between a sender and a recipient can be reused for successive communication tasks. In fact, from known results in physics, any system that exchanges information via the transfer of given physical resources, such as radio waves, particles and qubits, can conceivably reuse, at least part, of the received resources. This paper aims at illustrating some of the new challenges that arise in the design of communication networks in which the signals exchanged by the nodes carry both information and energy. To this end, a baseline two-way communication system is considered in which two nodes communicate in an interactive fashion. In the system, a node can either send an "onquotedblright symbol (or "1quotedblright), which costs one unit of energy, or an "offquotedblright signal (or "0quotedblright), which does not require any energy expenditure. Upon reception of a "1quotedblright signal, the recipient node "harvestsquotedblright, with some probability, the energy contained in the signal and stores it for future communication tasks. Inner and outer bounds on the achievable rates are derived. Numerical results demonstrate the effectiveness of the proposed strategies and illustrate some key design insights. [ABSTRACT FROM AUTHOR]

The modulation accuracy described by an error vector magnitude is a critical parameter in modern communication systems — defined originally as a performance metric for transmitters but now also used in receiver design and for more general signal analysis. The modulation accuracy is a measure of how far a test signal is from a reference signal at the symbol values when some parameters in a reconstruction model are optimized for best agreement. This paper provides an approach to computation of error vector magnitude as described in several standards from measured or simulated data. It is shown that the error vector magnitude optimization problem is generally non-convex. Robust estimation of the initial conditions for the optimizer is suggested, which is particularly important for a non-convex problem. A Bender decomposition approach is used to separate convex and non-convex parts of the problem to make the optimization procedure simpler and robust. A two step global optimization method is suggested where the global step is the grid method and the local method is the Newton method. A number of test cases are shown to illustrate the concepts. [ABSTRACT FROM PUBLISHER]

Unipolar communications systems can transmit information using only real and positive signals. This includes a variety of physical channels ranging from optical (fiber or free-space), to RF wireless using amplitude modulation with non-coherent reception, to baseband single wire communications. Unipolar OFDM techniques can efficiently compensate frequency selective channel distortion in unipolar communication systems. One of the leading example of unipolar OFDM is asymmetric clipped optical OFDM (ACO-OFDM) originally proposed for optical communications. Flip-OFDM is an alternative approach that was proposed in a patent, but its performance and full potentials have never been investigated in the literature. In this paper, we first compare Flip-OFDM and ACO-OFDM, and show that both techniques have the same performance but different complexities. In particular, Flip-OFDM offers 50% saving in hardware complexity at the receiver over ACO-OFDM. We then propose a new detection scheme, which enables to reduce the noise at the Flip-OFDM receiver by almost 3dB. The analytical performance of the noise filtering schemes is supported by the simulation results. [ABSTRACT FROM AUTHOR]

The optimal stochastic signaling based on the joint design of prior distribution and signal constellation is investigated under an average bit rate and power constraints. First, an optimization problem is formulated to maximize the average probability of correct decision over the set of joint distribution functions for prior probabilities and the corresponding constellation symbols. Next, an alternative problem formulation, for which the optimal joint distribution is characterized by a randomization among at most three mass points, is provided, and it is shown that both formulations share the same solution. Three special cases of the problem are investigated in detail. First, in the absence of randomization, the optimal prior probability distribution is analyzed for a given signal constellation and a closed-form solution is provided. Second, the optimal deterministic pair of prior probabilities and the corresponding signal levels are considered. Third, a binary communication system with scalar observations is investigated in the presence of a zero-mean additive white Gaussian noise, and the optimal solution is obtained under practical assumptions. Finally, numerical examples are presented to illustrate the theoretical results. It is observed that the proposed approach can provide improvements in terms of average symbol error rate over the classical scheme for certain scenarios. [ABSTRACT FROM AUTHOR]

We propose &#x201C.compressed training adaptive equalization” as a novel framework to reduce the quantity of training symbols in a communication packet. It is a semi-blind approach for communication systems employing time-domain/frequency-domain equalizers, and founded upon the idea of exploiting the magnitude boundedness of digital communication symbols. The corresponding algorithms are derived by combining the least-squares-cost-function measuring the training symbol reconstruction performance and the infinity-norm of the equalizer outputs as the cost for enforcing the special constellation boundedness property along the whole packet. In addition to providing a framework for developing effective adaptive equalization algorithms based on convex optimization, the proposed method establishes a direct link with compressed sensing by utilizing the duality of the \ell 1 and $\ell _\infty $ norms. This link enables the adaptation of recently emerged \ell 1 -norm-minimization-based algorithms and their analysis to the channel equalization problem. In particular, we show for noiseless/low noise scenarios, the required training length is on the order of the logarithm of the channel spread. Furthermore, we provide approximate performance analysis by invoking the recent MSE results from the sparsity-based data processing literature. Provided examples illustrate the significant training reductions by the proposed approach and demonstrate its potential for high bandwidth systems with fast mobility. [ABSTRACT FROM AUTHOR]

Data rate and energy efficiency decrement caused by the transmission of reference and data carrier signals in equal portions constitute the major drawback of differential chaos shift keying (DCSK) systems. To overcome this dominant drawback, a short reference DCSK system (SR-DCSK) is proposed. In SR-DCSK, the number of chaotic samples that constitute the reference signal is shortened to $R$ such that it occupies less than half of the bit duration. To build the transmitted data signal, $P$ concatenated replicas of $R$ are used to spread the data. This operation increases data rate and enhances energy efficiency without imposing extra complexity onto the system structure. The receiver uses its knowledge of the integers $R$ and $P$ to recover the data. The proposed system is analytically studied and the enhanced data rate and bit energy saving percentages are computed. Furthermore, theoretical performance for AWGN and multipath fading channels are derived and validated via simulation. In addition, optimising the length of the reference signal $R$ is exposed to detailed discussion and analysis. Finally, the application of the proposed short reference technique to the majority of transmit reference systems such as DCSK, multicarrier DCSK, and quadratic chaos shift keying enhances the overall performance of this class of chaotic modulations and is, therefore, promising. [ABSTRACT FROM PUBLISHER]

The problem of maximum likelihood (ML) detection in training-assisted single-input multiple-output (SIMO) systems with phase noise impairments is studied for two different scenarios, i.e., the case when the channel is deterministic and known (constant channel) and the case when the channel is stochastic and unknown (fading channel). Furthermore, two different operations with respect to the phase noise sources are considered, namely, the case of identical phase noise sources and the case of independent phase noise sources over the antennas. In all scenarios, the optimal detector is derived for a very general parameterization of the phase noise distribution. Furthermore, a high signal-to-noise-ratio (SNR) analysis is performed to show that symbol-error-rate (SER) floors appear in all cases. The SER floor in the case of identical phase noise sources (for both constant and fading channels) is independent of the number of antenna elements. In contrast, the SER floor in the case of independent phase noise sources is reduced when increasing the number of antenna elements (for both constant and fading channels). Finally, the system model is extended to multiple data channel uses and it is shown that the conclusion is valid for these setups, as well. [ABSTRACT FROM AUTHOR]

In this study, an optimal channel switching strategy is proposed for average capacity maximization in the presence of average and peak power constraints. Necessary and sufficient conditions are derived to determine when the proposed optimal channel switching strategy can or cannot outperform the optimal single channel strategy, which performs no channel switching. Also, it is obtained that the optimal channel switching strategy can be realized by channel switching between, at most, two different channels. In addition, a low-complexity optimization problem is derived to obtain the optimal channel switching strategy. Furthermore, based on some necessary conditions that need to be satisfied by the optimal channel switching solution, an alternative approach is proposed for calculating the optimal channel switching strategy. Numerical examples are provided to exemplify the derived theoretical results and to provide intuitive explanations. [ABSTRACT FROM PUBLISHER]

Optimal channel switching that provides the highest performance over a set of Gaussian channels with variable utilization costs is investigated in the presence of average power and average cost constraints. First, generic cost functions are considered, and it is shown that the optimal channel switching strategy performs channel switching (time sharing) among at most three different channels and always operates at the average power and average cost limits. Also, for channel switching between two channels, relations between the optimal power levels are obtained depending on the average power limit, and it is proved that the ratio of the optimal power levels is upper bounded by the ratio of the larger noise variance to the smaller one. In addition, for logarithmic cost functions, the convexity properties of the error probability are investigated as a function of power and cost, and the optimal channel switching strategy is shown to employ at most two channels, which can easily be determined based on specific formulas, when the average power limit is larger than a certain threshold. Numerical examples are presented to provide illustrations of the theoretical results. [ABSTRACT FROM PUBLISHER]

Networks need to accommodate diverse applications with different Quality-of-Service (QoS) requirements. New ideas at the physical layer are being developed for this purpose, such as diversity embedded coding, which is a technique that combines high rates with high reliability. We address the problem of how to fully utilize different rate-reliability characteristics at the physical layer to support different types of traffic over a network and to jointly maximize their utilities. We set up a new framework based on utility maximization for networks with composite links, meaning that each link consists of sub-links that can attain different rate-reliability characteristics simultaneously. We incorporate delay, in addition to rate and reliability, into the utility functions. To accommodate different types of traffic, we propose distributed algorithms converging to the optimal rate-reliability-delay tradeoff based on capacity division and priority queueing. Numerical results show that compared with traditional codes, the new codes can provide higher network utilities for all traffic types simultaneously. The results also show that priority queueing achieves higher network utility than capacity division. [ABSTRACT FROM AUTHOR]

We investigate a K-user parallel packet-erasure broadcast channel. There is an ongoing effort to harness millimeter-wave bands, which are known to be unstable having high outage probabilities, by combining them with stable legacy bands. Motivated by this effort, we consider a heterogeneous scenario in which the parallel subchannels are categorized into two classes having different outage probabilities. For the two-user case, we characterize the sum capacity by developing an explicit achievable scheme and deriving a matching upper bound. In contrast to suboptimal schemes that apply coding on a per-subchannel basis only, our scheme applies coding across subchannels to exploit coding opportunities that arise from asymmetric outage probabilities more efficiently, thereby achieving optimality. By extending our scheme systematically to be applicable for the K-user case, we show that it can provide significant gains over existing schemes. Compared to the K-user scheme currently employed in practice, which allocates chunks of subchannels to users exclusively, we demonstrate the performance improvement attainable by our scheme to be substantial, as the multiplicative gain scales with K. Moreover, we find that our scheme outperforms a per-subchannel extension of state-of-the-art K-user schemes by large margins, further reducing the optimality gap. Our results suggest a potential coding scheme that can be employed in future wireless systems to meet ever-growing mobile data demands. [ABSTRACT FROM AUTHOR]

Nonlinear device characteristics present a severe performance-bottleneck for several upcoming next-generation wireless communication systems and prevent them from delivering high data-rates to the end-users. In this context, reproducing kernel Hilbert space (RKHS) based signal processing methods have gained widespread deployment and have been found to outperform classical polynomial-filtering-based solutions significantly. Furthermore, recent RKHS based techniques that rely on explicit feature-maps called random Fourier features (RFF) have emerged. These techniques alleviate the dependence on learning a dictionary and avoid the computations and errors incurred in dictionary-based learning. However, the performance of existing RKHS based solutions depends on choosing a suitable kernel-width. For the widely-used Gaussian kernel, we propose a methodology of assigning kernel-bandwidths that capitalizes on a stochastic sampling of kernel-widths using an ensemble drawn from a pre-designed probability density function. The technique is found to deliver a comparable convergence/error-rate performance to the scenario when the kernel-width is chosen by brute-force trial and error for tuning it for best performance. The desirable properties of the proposed kernel-sampling technique are supported by analytical proofs and are further highlighted by computer-simulations presented in the form of case studies in the context of next-generation communication systems. [ABSTRACT FROM AUTHOR]

An unmanned aerial vehicle (UAV)-aided secure communication system is conceived and investigated, where the UAV transmits legitimate information to a ground user in the presence of an eavesdropper (Eve). To guarantee the security, the UAV employs a power splitting approach, where its transmit power can be divided into two parts for transmitting confidential messages and artificial noise (AN), respectively. We aim to maximize the average secrecy rate by jointly optimizing the UAV’s trajectory, the transmit power levels and the corresponding power splitting ratios allocated to different time slots during the whole flight time, subject to both the maximum UAV speed constraint, the total mobility energy constraint, the total transmit power constraint, and other related constraints. To efficiently tackle this non-convex optimization problem, we propose an iterative algorithm by blending the benefits of the block coordinate descent (BCD) method, the concave-convex procedure (CCCP) and the alternating direction method of multipliers (ADMM). Specially, we show that the proposed algorithm exhibits very low computational complexity and each of its updating steps can be formulated in a nearly closed form. Besides, it can be easily extended to the case of three-dimensional (3D) trajectory design. Our simulation results validate the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]