This paper investigates robust and secure active intelligent reflecting surface (IRS)-aided covert multi-user multiple-input multiple-output (MIMO) communications in the existence of a multi-antenna energy-harvesting eavesdropper. In particular, an active IRS is deployed to establish a favorable wireless communication environment for improving both security and covertness of the system. We aim to maximize the total system secrecy rate by jointly optimizing the transmit beamforming and artificial noise matrices at the base station (BS) and the reflection-coefficients of the active IRS. Furthermore, we formulate the design as a non-convex optimization problem, explicitly taking into account energy harvesting capabilities of the eavesdropper, information security requirements of legitimate users, and covertness constraint against adversarial detection. To address the inherent non-convexity of the optimization design problem, we propose an effective iterative suboptimal algorithm. In particular, we first transform the original optimization problem into a tractable form by employing the weighted minimum mean-square error (WMMSE), general sign-definiteness, and S-Procedure methods. Subsequently, we exploit the block coordinate descent (BCD) approach to decompose the coupled optimization matrices. Simulation results demonstrate that the proposed scheme can substantially outperform various baseline schemes adopting existing solutions. Besides, our results highlight the superiority of integrating active IRS into MIMO communication systems for secure and covert transmission.

This paper investigates the information-theoretic energy efficiency of intelligent reflecting surface (IRS)-aided wireless communication systems, taking into account the statistical quality-of-service (QoS) constraints on delay violation probabilities. Specifically, effective capacity is adopted to capture the maximum constant arrival rate that can be supported by a time-varying service process while fulfilling these statistical QoS requirements. We derive the minimum bit energy required for the IRS-aided wireless communication system under QoS constraints and analyze the spectral efficiency and energy efficiency tradeoff at low but nonzero signal-to-noise ratio (SNR) levels by also characterizing the wideband slope values. Our analysis demonstrates that the energy efficiency for the considered system under statistical QoS constraints can approach that for a system without QoS limitations in the low-SNR regime. Additionally, deploying a sufficiently large number of practical IRS reflecting elements can substantially reduce energy consumption required to achieve desired spectral efficiency performance in the low-power regime, even with limited bit-resolution phase shifters. Besides, we reveal that compared with the results applied to the low-power regime, higher effective capacity performance can be achieved in scenarios with sparse multipath fading while achieving the same minimum bit energy in the wideband regime.

This paper investigates resource allocation design for wideband integrated sensing and communication (ISAC) systems. We aim to minimize the Cramér-Rao Bound (CRB) for target estimation by jointly optimizing subcarrier allocation, digital beamforming matrices, and frequency-independent and frequency-dependent analog beamforming matrices at the base station (BS) adopting a hybrid beamforming structure. We formulate the optimization design as a non-convex mixed-integer nonlinear programming (MINLP) problem, subject to the transmit power budget constraint of the BS, the rate quality-of-service (QoS) constraints for users, and the discrete nature of the analog beamformer. To achieve a globally optimal solution for the complicated design problem, an iterative resource allocation algorithm is proposed by exploiting the generalized Bender's decomposition (GBD) method. Our simulation results demonstrate the crucial importance of simultaneously optimizing all available degrees-of-freedom (DoFs) in wideband ISAC systems jointly and optimally. Besides, our results unveil that deploying true-time-delayer (TTD) units with limited bit-resolution time delays can achieve substantial gains in both communication and sensing performances.

This paper investigates robust resource allocation design for active intelligent reflecting surface (IRS)-aided cognitive rate-splitting multiple access (C-RSMA) systems. In particular, an active IRS is deployed to shape a favorable wireless communication environment for enhancing the system performance. We aim to maximize the system energy efficiency by jointly optimizing the common rate allocations for the users, the transmit beamforming vectors at the coordinated base stations, and the active beamforming matrix at the IRS. We formulate the design as a non-convex optimization problem taking into account the discrete nature of the IRS elements and the transmit power budget constraints of the base stations as well as the active IRS. To tackle the non-convex design problem, a computationally effective iterative suboptimal algorithm is proposed by exploiting the block coordinate descent method, the generalized S-Procedure, the successive convex approximation, and the Dinkelbach’s approach. Simulation results reveal a non-trivial tradeoff between the system energy efficiency and the number of the IRS elements. Moreover, our results unveil that active IRS elements equipped with limited bit-resolution of discrete amplifiers and phase shifters is sufficient to achieve a significant gain in system energy efficiency.

This paper investigates resource allocation design for wideband integrated sensing and communication (ISAC) systems. To tackle the severe propagation attenuation issue in designing high-frequency ISAC systems, we adopt the hybrid beamformer at the transmitter to achieve substantial beamforming gains by generating highly directional beams. However, the well-known beam-split effect introduces multiple spatial directions at each subcarrier, due to the employment of wider bandwidth and a larger number of antennas, which may lead to system performance degradation. Fortunately, the notion of a true-time-delayer (TTD) has emerged as a crucial solution for compensating for the beam split by generating frequency-dependent phase shifts. To fully unleash its potential, we aim to minimize the Cramér-Rao Bound (CRB) for target estimation by jointly optimizing subcarrier allocation, digital beamforming matrices, and frequency-independent and frequency-dependent analog beamforming matrices at base station (BS). We formulate the optimization design as a non-convex mixed-integer non-linear programming (MINLP) problem, subject to the transmit power budget constraint of the BS, the rate quality-of-service (QoS) constraints for users, and the discrete nature of the analog beamformer. To achieve a globally optimal solution for the complex design problem, an iterative resource allocation algorithm is proposed by exploiting the generalized Bender’s decomposition (GBD) method. Moreover, we develop a computationally-efficient suboptimal algorithm to strike an effective balance between system performance and complexity. Our simulation results demonstrate the crucial importance of simultaneously optimizing all available degrees-of-freedom (DoFs) in wideband ISAC systems jointly and optimally. Furthermore, our proposed schemes are able to significantly improve the sensing accuracy over the traditional alternating optimization (AO) scheme adopted in existing solutions. Besides, our results unveil that deploying TTD units with limited bit-resolution time delays can achieve substantial gains in both communication and sensing performances.

In this paper, a fast hybrid automatic repeat request (HARQ) protocol is employed, where some HARQ feedback is omitted and the associated channel uses are incorporated for data transmission. Building upon this strategy, point-to-point communication systems which emphasize low delay and high reliability are revisited. Based on the established findings in finite blocklength (FBL) codes, systems employing the fast HARQ protocol operation under low transmission delay constraints and under low queueing delay constraints are explored, respectively. Then, long-term bit energy minimization problems are formulated. In light of the non-convex nature of the problem and the presence of small decoding error probabilities, finite-episode Markov Decision Process (MDP) with double-layer penalty rewards are established. Subsequently, an actor-critic based deep re-inforcement learning (DRL) algorithm is designed. Through numerical evaluations, it is shown that compared with the benchmark schemes, the proposed scheme is more energy efficient especially when the packet size is large. For the buffer-limited system with fast HARQ, there exists a coding rate that can optimize the energy efficiency.

In this paper, a secure wireless communication system, where a multi-antenna access point (AP) sends confidential information to a single-antenna user with the help of an untrusted relay adopting amplify-and-forward (AF) protocol and an IRS, is investigated. It is assumed that the link between the IRS and the untrusted relay is present. A secrecy rate maximization problem subject to the resource constraints at the AP and the untrusted relay is formulated. Then, an alternating iteration algorithm jointly optimizing the transmit beamforming matrix at the AP, the phase shifts of the IRS in two time slots and the relay beamforming matrix is proposed. Afterwards, the asymptotic expressions for the maximum secrecy rates of the proposed scheme in the high and low transmitted signal-to-noise ratio (SNR) regimes are derived as well. Finally, numerical evaluations demonstrate the superiority of the proposed scheme compared with other benchmark schemes, highlight the importance of properly designed phase shifts at the IRS, and validate the theoretical analysis.

This paper investigates robust resource allocation design for active intelligent reflecting surface (IRS)-aided cog-nitive rate-splitting multiple access (C-RSMA) systems. In particular, an active IRS is deployed to shape a favorable wireless communication environment for enhancing the system performance. We aim to maximize the system energy efficiency by jointly optimizing the common rate allocations for the users, the transmit beamforming vectors at the coordinated base stations, and the active beamforming matrix at the IRS. We formulate the resource allocation design as a non-convex optimization problem taking into account the discrete nature of the IRS elements and the transmit power budget constraints of the base stations as well as the active IRS. To tackle the non-convex design problem, we propose a computationally effective iterative suboptimal algorithm. Simulation results reveal a nontrivial tradeoff between the system energy efficiency and the number of the IRS elements. Moreover, our results unveil that active IRS elements equipped with limited bit-resolution of discrete amplifiers and phase shifters is sufficient to achieve a significant gain in the system energy efficiency.

In this paper, we develop a hybrid multiple access (MA) protocol for an intelligent reflecting surface (IRS) aided uplink transmission network by incorporating the IRS-aided time-division MA (I-TDMA) protocol and the IRS-aided non-orthogonal MA (I-NOMA) protocol as special cases. Two typical communication scenarios, namely the transmit power limited case and the transmit energy limited case are considered, where the device’s rearranged order, time and power allocation, as well as dynamic IRS beamforming patterns over time are jointly optimized to minimize the sum transmission delay. To shed light on the superiority of the proposed IRS-aided hybrid MA (I-HMA) protocol over conventional protocols, the conditions under which I-HMA outperforms I-TDMA and I-NOMA are revealed by characterizing their corresponding optimal solution. Then, a computationally efficient algorithm is proposed to obtain the high-quality solution to the corresponding optimization problems. Simulation results validate our theoretical findings, demonstrate the superiority of the proposed design, and draw some useful insights. Specifically, it is found that the proposed protocol can significantly reduce the sum transmission delay by combining the additional gain of dynamic IRS beamforming with the high spectral efficiency of NOMA, which thus reveals that integrating IRS into the proposed HMA protocol is an effective solution for delay-aware optimization. Furthermore, it reveals that the proposed design reduces the time consumption not only from the system-centric view, but also from the device-centric view.

In this work, we consider the minimization of the peak age of information violation probability in the wireless communication system. For any given sampling rate, the optimization of power adaptation is developed based on the control-communications co-design approach, which utilizes the inherent ability of control applications to tolerate a limited number of consecutive packet losses. A Markov chain failure model is established, and the mean time to failure (MTTF) is introduced as a performance metric for system reliability evaluation. A constrained Markov decision process (CMDP) problem is formulated and solved to obtain the optimal policy. Also, a suboptimal threshold-based policy is proposed. Numerical results show that the proposed optimal policy can increase the MTTF by orders of magnitude compared with benchmark schemes.

1In this paper, a downlink multi-user multiple-input multiple-output (MU-MIMO) system operating under statistical QoS constraints is investigated. Effective capacity, which is defined as the maximal constant arrival rate that can be supported by a given service process while satisfying the statistical queueing constraints, is adopted as the performance metric. Initially, perfect CSI is assumed at the base station (BS). An optimization problem is formulated to determine the optimal precoding matrix that maximizes the weighted sum effective capacity under total transmit power constraints at the BS. Then, an optimality condition that the optimal precoding matrix needs to satisfy is derived, which is proven to always have a feasible solution. Subsequently, fixed point iteration algorithms are designed to find a solution. Through extensive numerical results, the superiority of the proposed scheme is demonstrated under stringent delay constraints. Overall, this work provides an effective precoder design incorporating the statistical QoS constraints for the downlink MU-MIMO systems that outperforms existing strategies.

In this paper, an intelligent reflecting surface (IRS) assisted wireless secure communication system is studied. A multi-antenna access point (AP) intends to send confidential information to a single-antenna user in the presence of an amplify-and-forward (AF) untrusted relay, which may eavesdrop the message when helping relay the signal. It is assumed that the direct link between the AP and the user is blocked by the obstacles. The achievable secrecy rate maximization problem is then formulated. To overcome the non-convexity of the formulated problem, an alternating iteration algorithm is proposed to jointly optimize the active and passive beamforming. Specifically, the transmit beamforming vector at the AP, the phase shift matrix at the IRS, and the relay beamforming matrix are jointly optimized to maximize the secrecy rate. Moreover, the asymptotic expressions for the maximum secrecy rates of the proposed scheme in the high and low transmitted signal-to-noise ratio (SNR) regimes are derived as well. Finally, numerical evaluations demonstrate the superiority of the proposed scheme compared with other benchmark schemes, highlight the importance of properly designed phase shifts at the IRS, and validate the theoretical analysis. It is also demonstrated that the number of antennas at the AP should be strictly larger than the number of antennas at the relay to harvest the benefits of increasing the transmit power at the AP in increasing the secrecy rate.

Power control policies that minimize the weighted combination of age of information (AoI) and total energy consumption are studied in this paper. It is assumed that the status update information is acquired at the transmitter through sensors and then sent in packets to the receiver at fixed rate over Rayleigh fading channels. Retransmission mechanism is introduced to guarantee the reliability of the received update packets, and a limit on the maximum number of transmission rounds is imposed. On the one hand, with the channel distribution information (CDI) available at the transmitter, the age-energy tradeoff is optimized by formulating the problem as a constrained Markov decision process (CMDP) which takes into account the sensing power consumption as well as the average transmission power constraint. Employing the Lagrangian relaxation, the CMDP problem is transformed into an unconstrained Markov decision process (MDP) problem. A threshold-based policy is also provided. Subsequently, a dynamic programming approach is proposed to obtain the optimal power allocation policy. On the other hand, when the environment is unknown, two probabilistic reinforcement learning algorithms are proposed to optimize the age-energy tradeoff. Through simulation results, it is shown that the age-energy tradeoffs can be improved by the proposed optimal policies compared with benchmark schemes.

This paper considers secure communication in buffer-aided cooperative wireless networks in the presence of one eavesdropper, which can intercept the data transmission from both the source and relay nodes. A new max-ratio relaying protocol is proposed, in which different relays are chosen for reception and transmission according to the ratio of the legitimate channels to the eavesdropper channels, so that the relay selected for reception and the relay selected for transmission can receive and transmit at the same time. It is worth noting that the relay employs a randomize-and-forward (RF) strategy such that the eavesdropper can only decode the signals received in the two hops independently. Theoretical analysis of the secrecy throughput of the proposed scheme is provided and the approximate closed-form expressions are derived, which are verified by simulations. Through numerical results, it is shown that the proposed scheme achieves a significant improvement in secrecy throughput compared with existing relay selection policies.

In this paper, a multi-user system adopting finite blocklength (FBL) channel codes for downlink (DL) transmissions under quality-of-service (QoS) constraints is considered. A framework for minimizing the total bandwidth to ensure ultrareliable and low-latency communications (URLLC) between a transmitter and multiple users is established. Frequency-selective fading channels are considered. It is assumed that channel state information (CSI) is perfectly known at the receiver. Effective capacity framework is employed to characterize the throughput under delay constraints with FBL channel codes. The relationship between the throughput and the bandwidth is studied. The optimization problem to minimize the total bandwidth under different QoS and minimum throughput limits is formulated. Furthermore, an efficient algorithm to obtain the optimal bandwidth allocation scheme is proposed. Overall, the impact of delay exponents, decoding error probability and minimum throughput on URLLC is characterized.

In this paper, beamforming design based on a novel coverage model of high-speed railway (HSR) to improve the coverage in HSR communication systems is investigated. A dedicated coverage model, where the coverage cell is ellipse rather than the traditional circular is considered. Based on the elliptical coverage cell, an optimization problem for beamforming design is formulated to maximize the percentage of rail coverage for a given railway length, which is defined as the percentage of coverage distance that the signal-to-noise ratio (SNR) exceeds a desired SNR threshold for the given railway length, subject to the equal average received power on the elliptical line constraint. Considering that the percentage of coverage can be improved by increasing the received power, the problem can be recast to maximizing the expected average received power. A semidefinite relaxation (SDR) method is developed to solve the optimization problem. Through numerical results, the proposed elliptical coverage cell based beamforming can increase the covering railway distance and reduce the transmission power consumption compared with the circular coverage cell. It is also found that the larger eccentricity of the ellipse with appropriately chosen BS location can provide further coverage distance.

This paper investigates the performance of wireless systems that employ finite-blocklength channel codes for transmission and operate under queuing constraints in the form of limitations on buffer overflow or delay violation probabilities. A block fading model, in which fading stays constant in each coherence block and changes independently between blocks, is considered. It is assumed that channel coding is performed over multiple coherence blocks. A simple ARQ scheme with error-free feedback without any delay is considered. The channel coding rate with given maximal error probability 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 and fixed-rate transmissions is shown to be unique. The limiting performance as the number of blocks increases is characterized. The tradeoffs and the interactions between the throughput, the number of coherence blocks over which channel coding is performed, error probabilities, channel coherence duration, and queuing constraints are identified.

In this paper, the performance of indoor Terahertz (THz) communication systems with one-bit digital-to- analog converters (DACs) is investigated. Array-of- subarrays architecture is assumed for the antennas at the access points, where each RF chain uniquely activates a disjoint subset of antennas, each of which is connected to an exclusive phase shifter. Hybrid precoding, including maximum ratio transmission (MRT) and zero-forcing (ZF) precoding, is considered. The best beamsteering direction for the phase shifter in the large subarray antenna regime is first proved to be the direction of the line-of-sight (LoS) path. Subsequently, the closed-form expression of the lower- bound of the achievable rate in the large subarray antenna regime is derived, which is the same for both MRT and ZF and is independent of the transmit power. Numerical results validating the analysis are provided as well.

In this paper, we establish a comprehensive uplink system model for in-band and guard-band Narrowband Internet of Things (NB-IoT) with arbitrary sample duration in the NB-IoT device. The mathematical expressions of received LTE and NB-IoT signals are derived. Moreover, the close-form interference power on the LTE signal from the adjacent NB-IoT signal is given analytically. The result shows that the sample duration of NB-IoT device has significant impact on its desired signal and on the interference to the LTE user equipment (UE). Numerical results show that the analytical expressions match the simulated ones perfectly, which verifies the effectiveness of proposed system model and derivations. The work in this paper provides a valid guidance for NB-IoT system deployment and co-existence analysis.

In this paper, the outage performance of a single-cell two-tier mmWave cellular system employing joint spatial division and multiplexing (JSDM) are investigated. It is assumed that the macro base station (BS) equipped with a large number of antennas serve the single antenna pico BS (as a relay) and users simultaneously, and that the pico BS is located at the edge of the macro cell. Theoretical analysis of the signal-to- interference-plus-noise ratio (SINR) outage probability of each user is first obtained. The cell SINR outage probability is then derived. Simulation results demonstrating the performance improvement due to the relay introduced by the pico BS are provided. Overall, the impact of deploying pico BS in the single-cell mmWave cellular networks is characterized.

In this paper, the transmission scheme for the high speed railway (HSR) communication systems in the presence of Doppler shift is investigated. A fair transmission scheme based on sectored beams, in which there is little variation in the received signal-to- noise ratio (SNR), is proposed. An optimization problem for the beam design is formulated to maximize the expected average power within the beam coverage range with limited variation in the instantaneous received power in different locations. Through numerical results, the proposed transmission scheme is shown to achieve fair performance along the time. Overall, a location-fair solution for improving the fairness of the HSR communication systems is provided.

This paper studies the achievable throughput of fading multiple-access channels (MACs) with energy harvesting transmitters subject to statistical quality of service (QoS) constraints in the form of limitations on the buffer overflow probability. Effective capacity, which characterizes the maximum constant arrival rate that a given process can support while satisfying the QoS constraints, is employed as the performance metric. Perfect channel state information (CSI) and energy arrivals are assumed to be available at both the transmitters and the receiver. With the assumption of naive power control scheme, in which the transmission power level is irrespective of the CSI and decided by the instantaneous harvested energy, the effective throughput regions of time division multiple access and superposition coding (SC) with fixed decoding are characterized. In the special case of the same QoS constraints, the optimal decoding order strategy for SC with variable decoding order is obtained. With the assumption that the channel states and harvested energy in all time slots are known at the transmitters, the point-to-point link is first revisited. Then, for a given decoding order strategy in two-user MACs, a suboptimal power control policy based on the average energy arrivals and causal energy and channel information is proposed and shown to achieve performance close to the optimal one.

This paper investigates the link selection policy for secure communications over a buffer-aided two-hop communication link. It is assumed that a source wishes to send information to a destination with the aid of a trusted half-duplex relay node compromised by an eavesdropper, and that there is no direct link between the source and the destination. The buffer-aided relay forwards the information to the destination by employing the randomize-and-forward scheme. Both the source and the relay transmissions are assumed to be vulnerable to the eavesdropper. The perfect channel side information of the network is assumed to be available at the source and the relay. Initially, conventional relaying protocols where equal partition of the time for the reception and transmission of the relay is considered. Then, the optimal time fraction with the optimal power control policy that maximizes the secrecy throughput is identified. Moreover, the optimal joint link selection and power control policy that maximizes the secrecy throughput is derived. Subsequently, a low complexity and asymptotically optimal link selection with ON/OFF power control is proposed. Numerical results demonstrate that the proposed link selection policies with power control can significantly improve the achievable secrecy throughput of the buffer-aided two-hop communication system.

In this paper, transmission over buffer-aided diamond relay systems under statistical quality of service (QoS) constraints is studied. The statistical QoS constraints are imposed as limitations on delay violation probabilities. In the absence of channel state information (CSI) at the transmitter, truncated hybrid automatic repeat request-incremental redundancy (HARQ-IR) is incorporated to make better use of the wireless channel and the resources for each communication link. The packets that cannot be successfully received upon the maximum number of transmissions will be removed from buffer, i.e., outage occurs. The outage effective capacity is defined as the maximum constant arrival rate to the source that can be supported by the goodput departure processes, i.e., the departure that can be successfully received by the receiver. The outage effective capacity for the buffer-aided diamond relay system is obtained for HARQ-IR incorporated transmission strategy under the end-to-end delay constraints. In comparison with the decode-and-forward (DF) protocol with perfect CSI at the transmitters, it is shown that HARQ-IR can achieve better performance when the delay constraints are stringent.

In this paper, the achievable rate of buffer-aided diamond relay systems under delay constraints is studied. The effective capacity, characterizing the maximum constant arrival rate to the source while satisfying the statistical end-to-end delay constraints, is obtained for the conventional relay selection protocol, fixed decode-and-forward relaying schemes, and selective forwarding protocols. A selection forwarding policy that maximizes the delay exponent at the source is proposed, which is shown to be independent of delay constraints and select the relay with better channel conditions to forward the messages. Through numerical results, it is demonstrated that the selection forwarding strategy achieves superior performance than the conventional relay selection and fixed scheduling schemes under a variety of delay constraints.

In this paper, the achievable rate of buffer-aided diamond relay systems under delay constraints is studied. The effective capacity, characterizing the maximum constant arrival rate to the source while satisfying the end-to-end delay constraints, is obtained for fixed decode-and-forward (DF) relaying schemes and selective relaying protocols. A selection relaying policy that maximizes the delay exponent at the source is proposed, which is shown to be independent of delay constraints and select the relay with better channel conditions for reception. Through numerical results, it is demonstrated that the selection relaying strategy achieves superior performance than the fixed relaying schemes under a variety of delay constraints.

Power control policies in the fading multiple-access channels (MAC) with quality of service (QoS) constraints and random arrivals are studied. Perfect channel side information (CSI) is assumed to be available at both the transmitters and the receiver. Two types of Markovian sources, namely discrete Markov source and Markov fluid source, are considered. The maximum average arrival rates that can be supported in the fading multiple-access channel under QoS constraints are identified by incorporating the effective capacity of time-varying wireless transmission channels and effective bandwidth of random arrivals. The average throughput region is shown to be convex. Power control policies that maximize the weighted summation of the average arrival rates are characterized in the two-user case. Specifically, given the decoding order strategy, the conditions that the optimal power control policies must satisfy are determined, and an algorithm for the optimal power control policies is proposed for different source arrival models.

In this work, the achievable rate of three-node relay systems with selection relaying under statistical delay constraints, imposed on the limitations of the maximum end-to-end delay violation probabilities, is investigated. It is assumed that there are queues of infinite size at both the source and relay node, and the source can select the relay or destination for data reception. Given selection relaying policy, the effective bandwidth of the arrival processes of the queue at the relay is derived. Then, the maximum constant arrival rate can be identified as the maximum effective capacity as a function of the statistical end-to-end queueing delay constraints, signal-to-noise ratios (SNR) at the source and relay, the fading distributions of the links, and the relay policy. Subsequently, a relay policy that incorporates the statistical delay constraints is proposed. It is shown that the proposed relay policy can achieve better performance than existing protocols. Moreover, it is demonstrated that buffering relay model can still help improve the throughput of relay systems in the presence of statistical delay constraints and source-destination link.

This paper analyzes the impact of statistical delay constraints on the achievable rate of a two-hop wireless communication link in which the communication between a source and a destination is accomplished via a buffer-aided relay node. It is assumed that there is no direct link between the source and the destination, and the buffer-aided relay forwards the information to the destination by employing the decode-and-forward scheme. Given statistical delay constraints specified via maximum delay and delay violation probability, the tradeoff between the statistical delay constraints imposed on any two concatenated queues is identified. With this characterization, the maximum constant arrival rates that can be supported by this two-hop link are obtained by determining the effective capacity of such links as a function of the statistical delay constraints, signal-to-noise ratios at the source and relay, and the fading distributions of the links. It is shown that asymmetric statistical delay constraints at the buffers of the source and relay node can improve the achievable rate. Overall, the impact of the statistical delay tradeoff on the achievable throughput is provided.

This work analyzes the energy efficiency in fading channels under statistical delay constraints, imposed as limitations on the maximal delay violation probabilities. The maximum constant arrival rates are characterized with the aid of the notion of effective capacity, based on which the spectral efficiency-bit energy tradeoff is analyzed in the low-SNR regime. The analysis is performed under two assumptions: 1) perfect channel side information (CSI) at receiver only and 2) perfect CSI at both the transmitter and receiver. It is proven that the bit energy required at zero spectral efficiency is indeed the minimum bit energy. The expressions for the minimum bit energy and wideband slope are obtained. It is shown that the performances of the low-power and wideband regimes are the same, while the statistical queueing constraints have different behaviors. It is found that the minimum bit energy requirements increase as the statistical delay constraints become more stringent. Moreover, it is demonstrated that the minimum bit energy required is the same as that attained when only statistical queueing constraints are enforced in the wideband regime, while the bit energy increment is larger to achieve the same nonzero spectral efficiency. Overall, the impact upon the energy efficiency of statistical delay constraints is quantified.

Massive multiple-input multiple-output (MIMO) systems have attracted extensive attention recently due to their potentials to provide high system capacity. To obtain the benefits of massive MIMO systems, channel state information (CSI) at the transmitter is essential. The high overhead of traditional channel estimation and feedback scheme for downlink massive MIMO systems makes frequency division duplexing (FDD) impractical. Compressive sensing (CS) is a potential way to alleviate the problem. In this paper, we mainly focus on the CS- based feedback design. To guarantee the performance of the CS-based algorithms, a proper basis to reveal the sparsity of the channel is important. Here, we use the statistical information of the angle-of-departure (AoD) of physical channel paths for the basis design. A l0-norm based basis optimization problem is first formulated. Then, the problem is relaxed by a weighted l1-norm and is solved by an iterative algorithm. The mean-square-error (MSE) performance of the CS-based feedback scheme based on our proposed basis is better than the traditional discrete Fourier transform (DFT) basis.

In this work, the performance of two-hop wireless systems under statistical queueing \emph{end-to-end} delay constraints is investigated. In the two-hop links, it is assumed that there is no direct link between the source and destination. The communication between the source and destination is accomplished via an intermediate full-duplex relay node, which forwards the information to the destination by employing the decode-and-forward scheme. Both the queues at the source and relay node are subject to statistical queueing constraints imposed on the limitations of buffer violation probability. Given statistical delay constraints specified via maximum delay and delay violation probability, the tradeoff between the statistical delay constraints imposed to any two concatenated queues is identified. With this characterization, the maximum constant arrival rates that can be supported by this two-hop link are obtained by determining the effective capacity of such links as a function of the statistical delay constraints and signal-to-noise ratios (SNR) at the source and relay, and the fading distributions of the links. It is shown that the tradeoff between statistical delay constraints of the queues at the source and relay can improve the achievable rate. Also, compared with the performance achieved without buffer at the relay, the throughput with buffer at the relay can be larger for certain cases. Overall, the impact of statistical delay constraints on the achievable throughput is provided.

In this work, the achievable rate of three-node relay systems with selection relaying under statistical delay constraints, imposed on the limitations of the maximum delay violation probabilities, is investigated. It is assumed that there are queues of infinite size at both the source and relay node, and the source can select the relay or destination for data transmission. Given a selection relaying policy, the effective bandwidth of the arrival processes of the queue at the relay is derived. Then, the maximum constant arrival rate can be identified as the maximum effective capacity as a function of the statistical end-to-end queueing delay constraints and signal-to-noise ratios (SNR) at the source and relay, the fading distributions of the links, and the relay policy. Subsequently, a relay policy that incorporates the statistical delay constraints is proposed. It is shown that the proposed relay policy can achieve better performance than the one selecting the relay when source-relay link is stronger. Moreover, it is demonstrated that buffering relay model can still help improve the throughput of relay systems in the presence of statistical delay constraints and source-destination link.

In this paper, throughput of two-way relaying under buffer constraints is studied. In the two-way relay system, source nodes initially send their messages to the relay in the multiple-access phase. Relay decodes and stores the messages from different sources in different buffers and subsequently broadcasts a superimposed signal. It is assumed that both source nodes and the relay operate in the presence of statistical queueing constraints. Under these assumptions, arrival rates that can be supported in this system are investigated through the logarithmic moment generating functions of the arrival and service processes. In particular, after identifying the service rates in the multiple-access and broadcast phases and addressing the stability conditions, characterizations of the maximum arrival rates are provided in terms of system resource allocation parameters, signal-to-noise ratios, and quality-of-service exponents. Impact of different parameters on the performance is investigated through numerical results.

Transmission over fading broadcast and interference channels in the presence of quality of service (QoS) constraints is studied. Effective capacity, which provides the maximum constant arrival rate that a given service process can support while satisfying statistical QoS constraints, is employed as the performance metric. In the broadcast scenario, the effective capacity region achieved with superposition coding and successive interference cancellation is identified and is shown to be convex. Subsequently, optimal power control policies that achieve the boundary points of the effective capacity region are investigated, and an algorithm for the numerical computation of the optimal power adaptation schemes for the two-user case is provided. In the interference channel model, achievable throughput regions are determined for three different strategies, namely treating interference as noise, time division with power control and simultaneous decoding. It is demonstrated that as in Gaussian interference channels, simultaneous decoding expectedly performs better (i.e., supports higher arrival rates) when interfering links are strong, and treating interference as noise leads to improved performance when the interfering cross links are weak while time-division strategy should be preferred in between. When the QoS constraints become more stringent, it is observed that the sum-rates achieved by different schemes all diminish and approach each other, and time division with power control interestingly starts outperforming others over a wider range of cross-link strengths.

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.

Communication over fading interference channels in the presence of statistical quality of service (QoS) constraints is considered. Effective capacity, which provides the maximum constant arrival rate that a given service process can support while satisfying statistical queueing constraints, is employed as the performance metric. In a two-user and buffer constrained setting, arrival rate regions that can be supported in the fading interference channel are studied. More specifically, for three different strategies, namely treating interference as noise, time division with power control and simultaneous decoding, achievable throughput regions are determined. It is demonstrated that as in Gaussian interference channels, simultaneous decoding expectedly performs better (i.e., supports higher arrival rates) when interfering links are strong, and treating interference as noise leads to improved performance when the interfering cross links are weak while time-division strategy should be preferred in between. When the QoS constraints become more stringent, it is observed that the sum-rates achieved by different schemes all diminish and approach each other, and time division with power control interestingly starts outperforming others over a wider range of cross-link strengths.

In this paper, transmission over multiaccess fading channels under QoS constraints is studied in the low power regime. QoS constraints are imposed as limitations on the buffer violation probability. The effective capacity, which characterizes the maximum constant arrival rates in the presence of such statistical QoS constraints, is employed as the performance metric. The minimum received bit energy levels and wideband slope regions are characterized for different transmission and reception strategies, namely time-division multiple-access (TDMA), superposition coding with fixed decoding order, and superposition coding with variable decoding order. It is shown that the minimum received bit energies achieved by these different strategies are the same and independent of the QoS constraints. When wideband slope regions are considered, the suboptimality of TDMA with respect to superposition schemes is shown. For the case of superposition coding, it is proven that varying the decoding order at the receiver with the fading realizations does not enlarge the wideband slope region.

Effective capacity, which provides the maximum constant arrival rate that a given service process can support while satisfying statistical queueing constraints, is analyzed in a multiuser scenario. In particular, the effective capacity region of fading multiple-access channels in the presence of quality of service (QoS) constraints is studied. Perfect channel side information is assumed to be available at both the transmitters and the receiver. It is initially assumed that 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 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.

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.

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.

1Transmission over fading broadcast channels in the presence of quality of service (QoS) constraints is studied. Effective capacity, which provides the maximum constant arrival rate that a given service process can support while satisfying statistical QoS constraints, is employed as the performance metric. The effective capacity region achieved with superposition coding and successive interference cancellation is identified and is shown to be convex. Subsequently, optimal power control policies that achieve the boundary points of the effective capacity region are investigated, and an algorithm for the numerical computation of the optimal power adaptation schemes for the two-user case is provided. Additionally, performance attained with time-division multiplexing (TDM) of messages is studied for comparison with the optimal schemes.

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, 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, the 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 implying that time-sharing between any two viable transmission and power control strategies results in effective throughput values inside the region. 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. Additionally, the throughput region achieved by time-division multiplexing of common and confidential messages is explored. 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. These power adaptation policies are compared with the opportunistic ones that are optimal in the absence of quality of service (QoS) constraints. It is shown that opportunistic schemes, in which data transmission with high rates and high power occurs only when the main channel is much better than the eavesdropper channel, are no longer optimal under buffer constraints, and the transmitter should send the data at a certain moderate rate and power even when the main channel strength is comparable to that of the eavesdropper channel to avoid buffer overflows.

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. Considering 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.

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, secure transmission of information over an ergodic fading channel is studied in the presence of statistical quality of service (QoS) constraints.We employ effective capacity to measure the secure throughput of the system, i.e., effective secure throughput. We assume that the channel side information (CSI) of the main and the eavesdropper channels is available at the transmitter side. Under this assumption, we investigate the optimal power control policies that maximize the effective secure throughput. In particular, it is noted that opportunistic transmission is no longer optimal 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. Moreover, it is shown that the benefits of adapting the power with respect to the CSI of both the eavesdropper and main channels rather than the CSI of only the main channel diminish as QoS constraints become more stringent.

In this paper, a game-theoretic analysis for the resource allocation policies in fading multiple-access channels (MAC) in the presence of quality of service (QoS) constraints is performed. Effective capacity, which provides the maximum constant arrival rate, or throughput, that a given service process can support while satisfying statistical delay constraints, is considered in a multiuser scenario. We assume that the channel side information (CSI) is available at both the receiver and transmitters, and the transmitters are selfish, rational with certain QoS constraints and average power limitations. Without the aid of the receiver, we prove that there is always a unique admissible Nash equilibrium of the noncooperative power control game. The Nash equilibrium of the power control game is proved to be always inside the rate region where successive decoding techniques are used at the receiver.

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. On the other hand, it is proven that if sparse multipath fading with bounded number of independent resolvable paths is experienced, 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.

Transmission over wireless fading channels under quality of service (QoS) constraints is studied when only the receiver has perfect 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 arrival rate that a wireless channel can sustain while satisfying statistical QoS constraints. Energy efficiency is investigated by obtaining the minimum bit energy and wideband slope expressions in both low-power and wideband 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. Overall, an energy-delay tradeoff for fixed-rate transmission systems is provided.

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. The 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.

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). Initially, the wideband regime with multipath sparsity is investigated, and the minimum bit energy and wideband slope expressions are found. It is shown that the minimum bit energy requirements increase as the QoS constraints become more stringent. Subsequently, the low-power regime, which is also equivalent to the wideband regime with rich multipath fading, is analyzed. In this case, bit energy requirements are quantified through the expressions of bit energy required at zero spectral efficiency and wideband slope. It is shown for a certain class of fading distributions that the bit energy required at zero spectral efficiency is indeed the minimum bit energy for reliable communications. Moreover, it is proven that this minimum bit energy is attained in all cases regardless of the strictness of the QoS limitations. The impact upon the energy efficiency of multipath sparsity and richness is quantified, and comparisons with variable-rate/fixed-power and variable-rate/variable-power cases are provided.

Energy efficiency in fading channels in the presence of QoS constraints is studied. Effective capacity, which provides the maximum constant arrival rate that a given process can support while satisfying statistical delay 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, and energy requirements under QoS constraints are identified. The analysis is conducted for the case in which perfect channel side information (CSI) is available at the receiver and also for the case in which perfect CSI is available at both the receiver and transmitter. In particular, it is shown in the low-power regime that the minimum bit energy required in the presence of 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 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, an energy-delay tradeoff is characterized.