Statistical Delay Constraints Research Articles

Dynamic Resource Allocation for IRS Assisted Energy Harvesting Systems With Statistical Delay Constraint

In this paper, we develop centralized and distributed dynamic resource allocation schemes for an intelligent reflecting surface (IRS) aided energy harvesting (EH) system that optimize transmit power of a source node and phase-shift of passive reflecting elements of IRS. The source node randomly harvests renewable energy from the surrounding environment and performs data transmission with the harvested energy while satisfying statistical packet delay constraints in terms of maximum acceptable delay-outage probability. Our developed schemes do not require the statistical distributions of channel and energy profiles to be known and apply deep reinforcement learning (DRL) algorithm. Simulation results demonstrate the effectiveness of the proposed resource control scheme for IRS-aided EH system in different channel and energy conditions.

Edge-Cloud Collaboration Enabled Video Service Enhancement: A Hybrid Human-Artificial Intelligence Scheme

In this paper, a video service enhancement strategy is investigated under an edge-cloud collaboration framework, where video caching and delivery decisions are made at the cloud and edge respectively. We aim to guarantee the user fairness in terms of video coding rate under statistical delay constraint and edge caching capacity constraint. A hybrid human-artificial intelligence approach is developed to improve the user hit rate for video caching. Specifically, individual user interest is first characterized by merging factorization machine (FM) model and multi-layer perceptron (MLP) model, where both low-order and high-order features can be well learned simultaneously. Thereafter, a social aware similarity model is constructed to transfer individual user interest to group interest, based on which, videos can be selected to cache at the network edge. Furthermore, a dual bisection exploration scheme is proposed to optimize wireless resource allocation and video coding rate. The effectiveness of the proposed video caching and delivery scheme is finally validated by extensive experiments with a real-world dataset.

Performance Analysis of Uplink NOMA-Relevant Strategy Under Statistical Delay QoS Constraints

A new multiple access (MA) strategy, referred to as non orthogonal multiple access - Relevant (NOMA-R), allows selecting NOMA when this increases all individual rates, i.e., it is beneficial for both strong(er) and weak(er) individual users. This letter provides a performance analysis of the NOMA-R strategy in uplink networks with statistical delay constraints. Closed-form expressions of the effective capacity (EC) are provided in two-users networks, showing that the strong user always achieves a higher EC with NOMA-R. Regarding the network's sum EC, there are distinctive gains with NOMA-R, particularly under stringent delay constraints.

Effective Capacity in Wireless Networks: A Comprehensive Survey

Low latency applications, such as multimedia communications, autonomous vehicles, and Tactile Internet are the emerging applications for next-generation wireless networks, such as 5th generation (5G) mobile networks. Existing physical-layer channel models, however, do not explicitly consider quality-of-service (QoS) aware related parameters under specific delay constraints. To investigate the performance of low-latency applications in future networks, a new mathematical framework is needed. Effective capacity (EC), which is a link-layer channel model with QoS-awareness, can be used to investigate the performance of wireless networks under certain statistical delay constraints. In this paper, we provide a comprehensive survey on existing works, that use the EC model in various wireless networks. We summarize the work related to EC for different networks, such as cognitive radio networks (CRNs), cellular networks, relay networks, adhoc networks, and mesh networks. We explore five case studies encompassing EC operation with different design and architectural requirements. We survey various delay-sensitive applications, such as voice and video with their EC analysis under certain delay constraints. We finally present the future research directions with open issues covering EC maximization.

Resource Allocation in NOMA Virtualized Wireless Networks Under Statistical Delay Constraints

For 5G wireless communication networks, low latency and high spectral efficiency are required to provide ubiquitous communication for emerging applications. In this letter, we propose a novel framework which considers these requirements simultaneously by integrating the notion of effective capacity (EC) and non-orthogonal multiple access (NOMA) into virtualized wireless networks (VWNs). At first, we consider a virtual base station architecture to achieve isolation between different service providers (slices). Then, a resource allocation design for maximization of the EC is formulated as a non-convex optimization problem which takes into account the average maximum power constraints and delay quality-of-service requirements. To strike a balance between computational complexity and system performance, we apply the successive convex approximation to the non-convex optimization problem. Subsequently, an iterative low-complexity suboptimal algorithm is proposed. Numerical results illustrate that there is a non-trivial fundamental tradeoff between delay and spectral efficiency in VWNs while NOMA provides a significant improvement in terms of EC compared to conventional orthogonal multiple access.

Bound-based power optimization for multi-hop heterogeneous wireless industrial networks under statistical delay constraints

The noticeably increased deployment of wireless networks for battery-limited industrial applications in recent years highlights the need for tractable performance analysis methodologies as well as efficient QoS-aware transmit power management schemes. In this work, we seek to combine several important aspects of such networks, i.e., multi-hop connectivity, channel heterogeneity and the queuing effect, in order to address these needs. We design delay-bound-based algorithms for transmit power minimization and network lifetime maximization of multi-hop heterogeneous wireless networks using our previously developed stochastic network calculus approach for performance analysis of a cascade of buffered wireless fading channels. Our analysis shows an overall transmit power saving of up to 95% compared to a fixed power allocation scheme in case when the service is modeled via a Shannon capacity. For a more realistic set-up, we evaluate the performance of the suggested algorithm in a WirelessHART network, which is a widely used communication standard for industrial process automation applications. We find that link heterogeneity can significantly reduce network lifetime when no efficient power management is applied. Using extensive simulation study we further show that the proposed bound-based power allocation performs reasonably well compared to the real optimum, especially in the case of WirelessHART networks.

Quality-Driven Resource Allocation for Full-Duplex Delay-Constrained Wireless Video Transmissions

In this paper, wireless video transmission over full-duplex channels under total bandwidth and minimum required quality constraints is studied. In order to provide the desired performance levels to the end-users in real-time video transmissions, quality of service requirements such as statistical delay constraints are also considered. Effective capacity is used as the throughput metric in the presence of such statistical delay constraints since deterministic delay bounds are difficult to guarantee due to the time-varying nature of wireless fading channels. A communication scenario with multiple pairs of users in which different users have different delay requirements is addressed. Following characterizations from the rate-distortion theory, a logarithmic model of the quality-rate relation is used for predicting the quality of the reconstructed video in terms of the peak signal-to-noise ratio at the receiver side. Since the optimization problem is not concave or convex, the optimal bandwidth and power allocation policies that maximize the weighted sum video quality subject to total bandwidth, maximum transmission power level and minimum required quality constraints are derived by using monotonic optimization theory.

Adaptive Transmission for Coherent OWC With Multiple Parallel Optical Beams

We investigate adaptive transmission schemes for a coherent optical wireless communication system using multiple parallel optical beams. The proposed schemes perform adaptive modulation, transmit power allocation, and beam selection by considering statistical delay constraints. Our analysis and simulation results reveal the following three insights: 1) activating only suitable optical beams and adapting their transmission parameters significantly improve effective rate (ER) in strict delay constraint; 2) at both loose and strict delay constraints, equal power allocation among the suitable optical beams provides near optimal ER in high signal-to-noise-ratio (SNR) regimes; and 3) allocating all the power to the strongest optical beam provides near optimal ER at strict delay constraint and low SNR regimes.

Quality-Driven Resource Allocation for Wireless Video Transmissions Under Energy Efficiency and Delay Constraints

In this paper, wireless video transmissions are studied under total bandwidth and energy efficiency (EE) constraints. In order to provide the desired performance levels to the end-users in real-time video transmissions, quality of service requirements such as statistical delay constraints are also considered. Effective capacity is used as the throughput metric in the presence of such statistical delay constraints since deterministic delay bounds are difficult to guarantee due to the time-varying nature of wireless fading channels. A multiuser setup where different users have different delay guarantees is addressed. Following characterizations from the rate-distortion theory, a logarithmic model of the quality-rate relation is used for predicting the quality of the reconstructed video in terms of the peak signal-to-noise ratio at the receiver side. The optimal bandwidth allocation and the optimal power allocation/power control policies that maximize the sum video quality subject to total bandwidth and minimum EE constraints are derived. Five different resource allocation strategies are investigated, and simulation results show that the joint optimization of the bandwidth allocation and power control provides the best performance. The tradeoff between EE and video quality is also demonstrated since higher EE results in lower quality of received video sequence.

Statistical Delay Tradeoffs in Buffer-Aided Two-Hop Wireless Communication Systems

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 (SNR) 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.

Effective Capacity of Coherent POLMUX OWC Impaired by Atmospheric Turbulence and Pointing Errors

Effective capacity is defined as the maximum constant traffic arrival rate that a communication channel can support in order to guarantee a certain statistical delay constraint. We investigate the effective capacity performance of the optical wireless communications employing the coherent detection and polarization multiplexing over the Gamma–Gamma turbulence fading channels with pointing errors. We consider two different power adaptation techniques, namely, independent power adaptation and joint power adaptation. Closed-form effective capacity expressions are developed for both power adaptation schemes. Asymptotic analyses provide the increments of the effective capacities in the high signal-to-noise ratio regimes, in both nonstringent and stringent statistical delay constraints, for every 1 dB increase of the average transmit optical power. Our analysis reveals the superiority of the joint power-adaptation technique in order to support the stringent statistical delay constraint services over the optical wireless communication channels impaired by the strong turbulence fading and/or large pointing errors. However, the numerical results demonstrate that the performance gap between the joint and independent power adaptations becomes significantly reduced as the statistical delay constraints become loose and/or the channel impairments (i.e., turbulence fading and/or pointing error) become weak.

The Impact of Statistical Delay Constraints on the Energy Efficiency in Fading Channels

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.

Power Allocation for Buffer-Aided Full-Duplex Relaying With Imperfect Self-Interference Cancelation and Statistical Delay Constraint

This paper considers source and relay power allocation for buffer-aided full-duplex (B-FD) relaying network, assuming constant data rate arrivals at the source buffer. Statistical delay constraint is imposed, where the end-to-end queue length is allowed to exceed a pre-defined queue-length threshold with a maximum acceptable queue-length-outage probability. We assume imperfect self-interference (SI) cancelation, where the non-zero residual SI power is modeled to be proportional to the relay transmit power. We investigate two power allocation problems for source arrival rate maximization: 1) B-FD relaying with adaptive power allocation (B-FD-APA) when the instantaneous channel state information at the transmitters (CSIT) is available and 2) B-FD relaying with static power allocation (B-FD-SPA) when only the statistical CSIT is available. To solve the problems, we first employ asymptotic delay analysis to transform the statistical delay constraint into more tractable constraints. Then, the optimal solutions are derived using Lagrangian approach. In addition, solutions for various special cases of residual SI and delay constraint are presented. With B-FD-APA, the relay can opportunistically switch between half-duplex (HD) and FD operation modes according to the channel conditions. With B-FD-SPA, the relay always employs FD mode. Numerical results are performed to compare the capacities of the proposed B-FD, non-buffer FD, and buffer-aided HD relaying schemes, as well as direct transmission (DT) under various settings, demonstrating the effectiveness of B-FD relaying to support delay-constrained communications.

Effective Capacity of Buffer-Aided Full-Duplex Relay Systems With Selection Relaying

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.

Resource Allocation Under Delay-Guarantee Constraints for Visible-Light Communication

Visible light communications (VLCs) relying on commercially available light-emitting diode (LED) transmitters offer a huge data rate potential in this license-free spectral domain, while simultaneously satisfying energy-efficient conventional illumination demands. In an LED-based VLC system, the achievable data rate may be severely degraded owing to the interference, when the VLC system employs the unity frequency reuse (FR) approach. In order to mitigate the effects of interference, we propose a pair of interference avoidance approaches, namely, FR-based transmission and vectored transmission (VT). Furthermore, the resource allocation (RA) problems of indoor mobile terminals (MTs) are investigated based on different transmission strategies. Inspired by the concept of effective capacity (EC), we formulate our RA optimization problems applying proportional fairness, while satisfying specific statistical delay constraints. Our optimization procedure solves the RA problem of indoor MTs with the aid of a decentralized algorithm. Simulation results are also presented for quantifying the performance of the proposed algorithm. It is shown that both of our interference avoidance approaches are capable of reducing the interference, hence improving the overall performance. Furthermore, it is also observed that our VT transmission is capable of achieving a higher EC than the FR approach, when the statistical delay requirements are loose. By contrast, the FR-based transmission attains the best performance, when we tighten the delay requirements.

Resource Allocation Under Delay-Guarantee Constraints for Heterogeneous Visible-Light and RF Femtocell

The resource-allocation (RA) problems of mobile terminals (MTs) are investigated in a heterogeneous wireless network, where both a visible light communication system and an RF femtocell system are deployed in a room. We consider diverse quality-of-service requirements in terms of the data rate, fairness, and statistical delay requirements. Inspired by the concept of effective capacity, we formulate our optimization problems applying $\alpha$ -proportional fairness while satisfying specific statistical delay constraints. Two types of MTs, namely, multihoming MTs and multimode MTs, are considered, where multihoming MTs have the capability of aggregating resources from different networks, whereas the multimode MTs always select a single network for their connection. Our optimization procedure solves the RA probability problem for multihoming MTs with the aid of a decentralized algorithm. By contrast, our optimization problem involves both network selection and RA probability optimization for multimode MTs, which may be regarded as a mixed-integer nonlinear problem. Since this problem is computationally intractable, a suboptimal decentralized method is proposed for solving it. Simulation results are also presented for clarifying the performance of the proposed algorithm. It is shown that the multimode MTs are capable of achieving similar performance to that of the multihoming MTs when the statistical delay requirements are loose. However, as expected, the multihoming MTs attain a better performance when we tighten the delay requirements.

Design and Analysis of Distributed Hopping-Based Channel Access in Multi-Channel Cognitive Radio Systems with Delay Constraints

To support delay-sensitive traffic in multi-channel cognitive radio systems, designing a channel access scheme faces two major challenges, namely, the long waiting time due to continuous channel occupancy of primary users (PUs) and the performance degradation due to transmission collisions among secondary users (SUs). To address both issues, we propose a two-phase channel access scheme, which consists of a distributed channel negotiation phase and a hopping-based channel access phase for each SU. Specifically, in its first phase, an SU attempts to negotiate a specific initial slot/channel differing from the ones chosen by other SUs. Then, in its second phase, the SU chooses a channel in each time slot in a hopping-based manner to transmit data, where the hopping starts from its initial channel and follows a common hopping sequence. Virtual channels are introduced to accommodate the situation when the number of SUs is larger than that of actual channels. The average maximal waiting time due to the channel negotiation phase is derived, and the effective capacity of the service process for each SU in the channel access phase is analyzed. Numerical results show that the proposed scheme can support a higher traffic load under the statistical delay constraint, as compared with fixed or random channel access schemes.

Queuing analysis in amplify-and-forward cooperative diversity wireless networks with random feedback delay

This paper analyzes the performance of cooperative diversity wireless networks using amplify-and-forward relaying over independent, non-identical, Nakagami-m fading channels. We present a queuing model for performance analysis of go-back-N automatic repeat request (GBN-ARQ) protocols in wireless networks using dynamic radio link adaptation. Link adaptation technique allows multi-rate transmission which is assumed to be achieved through adaptive modulation and coding. We propose a Markov-based model, which encompasses the following aspects: (1) the transmission using amplify-and-forward cooperative diversity at the physical layer; (2) a flow control protocol, infinite transmitting buffers, and an ARQ-based error recovery mechanism at the radio link layer. The randomly changed feedback delay in cooperative diversity wireless networks is analyzed. The queuing problem is formulated as a GI/M/1 Markov chain where the exact queue length and delay statistics for the GBN-ARQ protocol can be obtained by using matrix geometric methods under random feedback delay values. We validate the analysis by simulation. The delay statistics obtained in this paper enables us to design wireless systems under statistical delay constraints and would be useful to predict the higher layer protocol performance.

Joint routing and admission control problem under statistical delay and jitter constraints in MPLS networks

Admission control algorithms are crucial for ensuring a near optimal resource allocation while guaranteeing the required Quality of Service (QoS) constraints. In this paper, a new routing and Admission Control mechanism in multi-protocol label switching (MPLS) based networks is proposed. The proposed mechanism relies on the packets’ delay distributions that are empirically built on every link, to make adequate admission decisions. As a new connection request arrives, the admission control mechanism computes a feasible path, satisfying the connection’s statistical QoS constraints (the maximum end-to-end delay, jitter and the QoS violation probability). For that, we formulate this problem as an Integer Linear Programming (ILP) model that is solved to optimality using the CPLEX mathematical programming tool for real-size networks. Simulation results show that the new admission control mechanism allows for low blocking rates while statistically satisfying the QoS constraints for both the new and the ongoing connections.

Queueing Analysis for GBN and SR ARQ Protocols under Dynamic Radio Link Adaptation with Non-Zero Feedback Delay

We present a queueing model for performance analysis of go-back-N (GBN) and selective repeat (SR) automatic repeat request (ARQ) protocols in wireless networks using dynamic radio link adaptation with non-instantaneous feedback. Link adaptation technique allows multi-rate transmission which is assumed to be achieved through adaptive modulation and coding. The radio link level queueing models for these two ARQ protocols are formulated in discrete time where the exact queue length and the delay statistics are obtained by using matrix geometric methods under different feedback delay values, channel and system parameters. The link layer delay statistics are useful in many ways, for example, to perform packet level admission control under statistical delay constraints. We validate the analysis by simulation and discuss useful implications of the analytical model on system performance. For dynamic link adaptation, the mode switching thresholds for the received signal-to-noise ratio (SNR) can be chosen to obtain very good link level delay performance. This SNR partitioning is shown to achieve significant cross-layer design gain compared to the case where the mode switching thresholds are chosen to maximize the physical layer throughput.