Finite Blocklength Regime Research Articles

Joint computation and power allocation for NOMA enabled MEC networks in the finite blocklength regime

This paper investigates the reliable computation offloading in non-orthogonal multiple access enabled mobile edge computing networks, where the short-packet technique is adopted to meet the stringent latency requirements of delay-sensitive computing services. To characterize the reliability of computation offloading with finite blocklength coding, a novel analytical framework is developed to approximate the average overall block error probability (AOBEP) by using a double-case linearization. With the derived approximate expression for AOBEP, the joint optimization of computation workload and transmit power is further investigated, in order to minimize the AOBEP under the computation/communication delay constraints. To tackle the non-convexity of the formulated problem, the formulated problem is first decomposed into the computation workload problem and the transmit power allocation problem. For the computing workload problem, a closed-form solution is derived. Then, by applying the derived workload allocation, the power allocation is transformed into the convex form through some approximations and solved by the successive convex approximation technique. Finally, simulation results are provided to demonstrate the reliability enhancement of computation offloading and reveal the relationship between the workload/power allocation and the communication/computation delay.

Information Age-Delay Correlation and Optimization With Finite Block Length

Both information age and delay are critical performance metrics of emerging time-sensitive applications. However, their inherent correlation in the finite block length (FBL) regime has remained uninvestigated as it is affected by block length and update rate in a complex manner. In this paper, closed-form expressions for average age of information (AoI), peak AoI (PAoI) and delay are derived for an FBL Last-Come First-Served system with retransmission and non-preemption policies, based on which a comprehensive analysis of the relationship among the three metrics in the FBL regime is presented. It is proved that there exists a strong tradeoff between delay and AoI/PAoI given a block length, and that AoI, PAoI and delay have positive correlation given an update rate, regardless of the weight. With the goal of minimizing delay and AoI simultaneously, the weighted sum of delay and PAoI (upper bound on AoI) is formulated and proved to be convex with respect to block length and update rate. A low-complexity optimization algorithm is developed with a closed-form expression of the optimal update rate, whose performance approaches the Pareto boundaries of the PAoI-delay and the AoI-delay regions, at much lower complexity than exhaustive search.

Average Rate and Error Probability Analysis in Short Packet Communications Over RIS-Aided URLLC Systems

In this paper, the average achievable rate and error probability of a reconfigurable intelligent surface (RIS) aided systems is investigated for the finite blocklength (FBL) regime. The performance loss due to the presence of phase errors arising from limited quantization levels as well as hardware impairments at the RIS elements is also discussed. First, the composite channel containing the direct path plus the product of reflected channels through the RIS is characterized. Then, the distribution of the received signal-to-noise ratio (SNR) is matched to a Gamma random variable whose parameters depend on the total number of RIS elements, phase errors and the channels' path loss. Next, by considering the FBL regime, the achievable rate expression and error probability are identified and the corresponding average rate and average error probability are elaborated based on the proposed SNR distribution. Furthermore, the impact of the presence of phase error due to either limited quantization levels or hardware impairments on the average rate and error probability is discussed. The numerical results show that Monte Carlo simulations conform to matched Gamma distribution to received SNR for sufficiently large number of RIS elements. In addition, the system reliability indicated by the tightness of the SNR distribution increases when RIS is leveraged particularly when only the reflected channel exists. This highlights the advantages of RIS-aided communications for ultra-reliable and low-latency systems. The difference between Shannon capacity and achievable rate in FBL regime is also discussed. Additionally, the required number of RIS elements to achieve a desired error probability in the FBL regime will be significantly reduced when the phase shifts are performed without error.

NOMA-based UAV system under finite blocklength regime with analysis in Rician fading channel

The finite blocklength (FBL) communication has been studied for quite some time for the fifth generation of cellular networks (5G). Though, the research in FBL is still in early stage due to the fact that 5G requires high reliability of almost 99.9999% with latency of less than 1 ms, simultaneously. The FBL has been worked upon to reduce latency such that Shannon's capacity expression is no longer applicable. The 5G claims to provide connectivity everywhere, hence to increase the coverage to remote places Unmanned Ariel Vehicle (UAV) has gained attention due to its low cost, mobility, and air time. In this paper, a scenario where a UAV relays data from a base station (BS) to remote users (RU), which are otherwise not in direct contact, is analyzed. All the communications among BS, UAV, and RU's are considered to be non-orthogonal multiple access (NOMA) based with Finite blocklength (FBL). An exact closed form expression for end-to-end average block error rate (BLER) is derived for above mentioned scenario and verified by extensive simulations. In addition, an asymptotic BLER for remote users at high transmission Signal to noise ratio is also derived. Further, the BLER is minimized to jointly optimize the power allocation coefficients, position of UAV and Blocklength for the communication system. The effects of different parameters on average BLER, position, and power are studied and the coverage provided by UAV for given probability of error is presented.

Covert communication with beamforming over MISO channels in the finite blocklength regime

Covert communication with beamforming over MISO channels in the finite blocklength regime

Effective Energy Efficiency of Ultrareliable Low-Latency Communication

Effective capacity (EC) defines the maximum communication rate subject to a specific delay constraint, while effective energy efficiency (EEE) indicates the ratio between EC and power consumption. We analyze the EEE of ultrareliable networks operating in the finite-blocklength regime. We obtain a closed-form approximation for the EEE in quasistatic Nakagami- m (and Rayleigh as subcase) fading channels as a function of power, error probability, and latency. Furthermore, we characterize the quality-of-service constrained EEE maximization problem for different power consumption models, which shows a significant difference between finite and infinite-blocklength coding with respect to EEE and optimal power allocation strategy. As asserted in the literature, achieving ultrareliability using one transmission consumes a huge amount of power, which is not applicable for energy limited Internet-of-Things devices. In this context, accounting for empty buffer probability in machine-type communication (MTC) and extending the maximum delay tolerance jointly enhances the EEE and allows for adaptive retransmission of faulty packets. Our analysis reveals that obtaining the optimum error probability for each transmission by minimizing the nonempty buffer probability approaches EEE optimality, while being analytically tractable via Dinkelbach's algorithm. Furthermore, the results illustrate the power saving and the significant EEE gain attained by applying adaptive retransmission protocols, while sacrificing a limited increase in latency.

Delay-Sensitive NOMA-HARQ for Short Packet Communications.

This paper investigates the two-user uplink non-orthogonal multiple access (NOMA) paired with the hybrid automatic repeat request (HARQ) in the finite blocklength regime, where the target latency of each user is the priority. To limit the packet delivery delay and avoid packet queuing of the users, we propose a novel NOMA-HARQ approach where the retransmission of each packet is served non-orthogonally with the new packet in the same time slot. We use a Markov model (MM) to analyze the dynamics of the uplink NOMA-HARQ with one retransmission and characterize the packet error rate (PER), throughput, and latency performance of each user. We also present numerical optimizations to find the optimal power ratios of each user. Numerical results show that the proposed scheme significantly outperforms the standard NOMA-HARQ in terms of packet delivery delay at the target PER.

Secrecy Throughput in Full-Duplex Multiuser MIMO Short-Packet Communications

In this letter, we consider the physical-layer security (PLS) in full-duplex (FD) multiuser multiple-input-multiple-output (MIMO) short-packet communications, where a base station (BS) transmits precoded signals for secure downlink multicast while receiving signals from uplink users. To quantify the PLS performance in the worst-case scenario, we consider the possible maximum wiretapping capability of a multi-antenna eavesdropper. Taking into account the self-interference (SI) in FD mode and the co-channel interference (CCI) from uplink to downlink, we analyst the secrecy throughput in finite blocklength regime and obtain its analytic expression, which perfectly matches asymptotic and simulation results in various scenarios. Moreover, the investigations on secrecy throughput substantiate that the FD multiuser MIMO systems outperform their half-duplex counterparts given the SI being sufficiently suppressed and the CCI being well managed.

MIMO Design for Internet of Things: Joint Optimization of Spectral Efficiency and Error Probability in Finite Blocklength Regime

In this article, we consider a multiple-input–multiple-output (MIMO) system serving Internet of Things (IoT) devices. To satisfy stringent requirements on the latency of IoT communications, the IoT devices communicate in the finite blocklength regime, wherein the achievable spectral efficiency (SE) has a backoff factor and decoding error probability is nonnegligible. Aiming to jointly optimize the sum SE and the maximum error probability, we first express the achievable SE as a function of the channel coefficients, precoders, and error probabilities. Subsequently, we formulate a problem with respect to precoders and error probabilities. A straightforward approach for the formulated problem, however, is challenging as it not only has multiple objectives but also is nonconvex. To resolve these issues, we first transform the problem as a single-objective optimization by using a weighted sum approach. Based on the reformulation, we propose an algorithm, in which error probabilities and precoders are determined by alternating two phases. Via simulations, we demonstrate that the proposed method offers significant gains compared to baseline methods, in terms of the achievable SE and the maximum error probability. In particular, we show that the communication latency is greatly reduced by using the proposed method.

Reliability-Optimal Offloading in Low-Latency Edge Computing Networks: Analytical and Reinforcement Learning Based Designs

In this paper, we consider a multi-access edge computing (MEC) network with multiple servers. Due to the low latency constraints, the wireless data transmission/offloading is carried by finite blocklength codes. We characterize the reliability of the transmission phase in the finite blocklength regime and investigate the extreme event of queue length violation in the computation phase by applying extreme value theory. Under the assumption of perfect channel state information (CSI), we follow the obtained characterizations and provide an optimal framework design including server selection and time allocation aiming to minimize the overall error probability. Moreover, when only the outdated CSI is available, a deep reinforcement learning based design is proposed applying the deep deterministic policy gradient method. Via simulations, we validate the convexity proven in our analytical model and show the performance advantage of proposed analytical solution and learning-based solution comparing to the benchmark for perfect CSI and outdated CSI, respectively.

Symbol-Level Precoding With Constellation Rotation in the Finite Block Length Regime

This letter tackles the problem of optimizing the parameters of a symbol-level precoder for downlink multi-antenna multi-user systems in the finite block length regime. Symbol-level precoding (SLP) is a non-linear technique for multi-user wireless networks, which exploits constructive interference among co-channel links. Current SLP designs, however, implicitly assume asymptotically infinite blocks, since they do not take into account that the design rules for finite and especially short blocks might significantly differ. This letter fills this gap by introducing a novel SLP design based on discrete constellation rotations. The rotations are the added degree of freedom that can be optimized for every block to be transmitted, for instance, to save transmit power. Numerical evaluations of the proposed method indicate substantial power savings, which might be over 99% compared to the traditional SLP, at the expense of a single additional pilot symbol per block for constellation de-rotation.

Optimal Resource Allocations for Statistical QoS Provisioning to Support mURLLC Over FBC-EH-Based 6G THz Wireless Nano-Networks

One of most important techniques for enabling the sixth-generation (6G) mobile wireless network lies in how to efficiently guarantee various stringent quality-of-service (QoS) performance-metrics to support the emerging massive Ultra-Reliable Low-Latency Communications (mURLLC) in 6G. Correspondingly, finite blocklength coding (FBC) has been developed as an effective technique to significantly improve various QoS indices for mURLLC through implementing short-packet communications. On the other hand, Terahertz (THz) band wireless nano-communications have been widely envisioned as a promising 6G technique to efficiently support utra-high data-rate (up to 1 Tbps). One of the major constraints over THz-band nano-networks is the severely limited energy that can be accessed by nano devices. Towards this end, various novel energy harvesting (EH) mechanisms have been proposed to remedy the energy scarcity problem. However, how to accurately characterize the relationships among THz wireless channels, energy consumption, and EH models for FBC based nano communications remains a challenging problem to support statistical delay and error-rate bounded QoS provisioning over FBC based 6G THz wireless nano-networks. To overcome these challenges, in this paper we propose optimal resource allocation policies to achieve the maximum ε-effective capacity in the THz band over FBC-EH-based nano-networks. Particularly, we establish nano-scale system models and characterize wireless channel models in the THz band using FBC. In order to support statistical delay and error-rate bounded QoS provisioning, we formulate and solve the ε-effective capacity maximization problem under several different EH constraints for our proposed schemes. Simulation results are included, which validate and evaluate our proposed schemes in the finite blocklength regime.

Error Probability Bounds for Gaussian Channels Under Maximal and Average Power Constraints

This paper studies the performance of block coding on an additive white Gaussian noise channel under different power limitations at the transmitter. New lower bounds are presented for the minimum error probability of codes satisfying maximal and average power constraints. These bounds are tighter than previous results in the finite blocklength regime, and yield a better understanding on the structure of good codes under an average power limitation. Evaluation of these bounds for short and moderate blocklengths is also discussed.

Resource allocation for massive machine type communications in the finite blocklength regime

Massive machine type communications (mMTC) have been regarded as promising applications in the future. One main feature of mMTC is short packet communication. Different from traditional long packet communication, short packet communication suffers from transmission rate degradation and a significant error rate is introduced. In this case, traditional resource allocation scheme for mMTC is no longer applicable. In this paper, we explore resource allocation for cellular-based mMTC in the finite block- length regime. First, to mitigate the load of the base station (BS), we establish a framework for cellular- based mMTC, where MTCGs reuse the resources of cellular users (CUs), aggregate the packets generated by MTCDs, and forward them to the BS. Next, we adopt short packet theory to obtain the minimum required blocklength of a packet that transmits a certain amount of information. Then, by modeling the process of MTCGs-assisted communication as a queuing process, we derive the closed-form expression of the average delay of all MTCDs. Guided by this, we propose a joint power allocation and spectrum sharing scheme to minimize the average delay. Finally, the simulation results verify the correctness of the theoretical results and show that the proposed scheme can reduce the average delay efficiently.

URLLC-Oriented Joint Power Control and Resource Allocation in UAV-Assisted Networks

Recently, ultrareliable and low-latency communication (URLLC) has attracted a significant interest for mission-critical applications in future wireless communication systems. Achieving strict requirements of latency and reliability for URLLC with a fixed infrastructure is challenging, and unmanned aerial vehicles (UAVs) have been deemed as promising enablers to handle this issue due to its salient attributes, such as high maneuverability, flexible deployment, and high probability of line-of-sight links. This article investigates a novel UAV-assisted URLLC service system, where the blocklength of channel codes is finite in Internet-of-Things (IoT) networks. Considering the limited energy of IoT devices, the average uplink transmit power of the IoT devices are minimized by jointly optimizing the device scheduling and association, power control and resource allocation, as well as UAV deployment. The formulated problem is a mixed-integer nonconvex optimization problem because of the finite blocklength regime. To tackle the problem, we derive the approximation of the achievable rate and propose an effective iteration algorithm by applying the block coordinate descent (BCD) and Lagrange dual decomposition techniques. Furthermore, the convergence of our proposed algorithm is analyzed and illustrated. The minimum average transmit power of IoT devices is calculated with a different resource allocation scheme. Simulation results demonstrate that our proposed iterative algorithm can obtain a performance gain of 15%–20% in terms of the average transmit power for URLLC. Moreover, compared with the average bandwidth allocation scheme, our proposed algorithm can get a stable minimum as the total bandwidth increases.

Finite Blocklength Analysis of Energy Harvesting Channels

We consider additive white Gaussian noise channels and discrete memoryless channels where the transmitter harvests energy from the environment. These can model wireless sensor networks as well as Internet of Things. By providing a unifying framework that works for any energy harvesting channel, we study these channels assuming an infinite energy buffer and provide the corresponding achievability and converse bounds on the channel capacity in the finite blocklength regime. We additionally provide moderate deviation asymptotic bounds.

Performance Analysis of URLL Energy-Harvesting Cognitive-Radio IoT Networks With Short Packet and Diversity Transmissions

The advent of the Internet-of-Things (IoT) and proliferation of wireless devices and systems have put stringent requirements on reliability and latency, in addition to the scarcity of energy and spectrum resources. More importantly, ultra-reliability and low-latency (URLL) combined with concepts of energy-harvesting (EH) and cognitive-radio (CR) make the analysis of IoT networks much more complex. This paper analyzes the performance of uplink EH-CR-IoT networks with URLL requirements. Analytical expressions for IoT network metrics, namely, average packet latency, reliability, and energy-efficiency are derived, while incorporating diversity transmissions under the finite blocklength (FBL) regime. The effect of network parameters, such as number of resource blocks allocated to each IoT user equipment (UE), blocklength, and number of packet replicas is examined on the network metrics, and their tradeoffs are discussed. Finally, the derived expressions are utilized to maximize the energy-efficiency of the IoT UEs subject to energy-causality and URLL constraints.

Random Access Channel Coding in the Finite Blocklength Regime

Consider a random access communication scenario over a channel whose operation is defined for any number of possible transmitters. As in the model recently introduced by Polyanskiy for the Multiple Access Channel (MAC) with a fixed, known number of transmitters, the channel is assumed to be invariant to permutations on its inputs, and all active transmitters employ identical encoders. Unlike the Polyanskiy model, in the proposed scenario, neither the transmitters nor the receiver knows which transmitters are active. We refer to this agnostic communication setup as the Random Access Channel (RAC). Scheduled feedback of a finite number of bits is used to synchronize the transmitters. The decoder is tasked with determining from the channel output the number of active transmitters, $k$, and their messages but not which transmitter sent which message. The decoding procedure occurs at a time $n_t$ depending on the decoder's estimate, $t$, of the number of active transmitters, $k$, thereby achieving a rate that varies with the number of active transmitters. Single-bit feedback at each time $n_i, i \leq t$, enables all transmitters to determine the end of one coding epoch and the start of the next. The central result of this work demonstrates the achievability on a RAC of performance that is first-order optimal for the MAC in operation during each coding epoch. While prior multiple access schemes for a fixed number of transmitters require $2^k - 1$ simultaneous threshold rules, the proposed scheme uses a single threshold rule and achieves the same dispersion.

Covert Communications With Channel Inversion Power Control in the Finite Blocklength Regime

In this letter, we investigate covert communications with finite blocklength under the channel inversion power control (CIPC) scheme, where a transmitter is allowed to communicate with a receiver without transmitting the pilot signals, which facilitates the hidden of the transmitter from the warden. Considering both the conventional and truncated CIPC schemes, we provide the novel expressions of the optimal detection threshold and the minimum total error probability at the warden. Furthermore, the optimization of the power control parameter at the transmitter is presented to maximize the effective covert throughput, which quantifies the amount of the information bits transmitted from the transmitter to the receiver subject to the covert constraint, under two kinds of CIPC schemes.

NOMA Versus OMA in Finite Blocklength Regime: Link-Layer Rate Performance

In this article, we investigate the latency performance of non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) technologies in finite blocklength regime. In the comparative study, we derive the achievable effective capacity of two-user NOMA and its OMA counterpart under delay quality-of-service constraints. We then obtain closed-form expressions for the achievable effective capacity of the weak and strong users in both scenarios considering transmissions over Rayleigh fading channels. Numerical results are provided. In particular, it is shown that at low signal-to-noise ratios (SNRs), the OMA user with better channel condition outperforms both NOMA users. We also evaluate the impact of fixed power allocation scheme on the achievable effective capacity of two-user NOMA. The comparative analysis of the total link-layer rate shows that at high SNRs, the total link-layer rate of NOMA with finite blocklength outperforms the one of OMA when the delay exponent is loose.