Information Theory (cs.IT)

Abstract: As the size of transistors approaches the mesoscopic scale, existing energy consumption analysis methods exhibit various limits, especially when being applied to describe the non-equilibrium information processing of transistors at ultra-low voltages. The stochastic thermodynamics offers a theoretic tool to analyze the energy consumption of transistor during the non-equilibrium information processing. Based on this theory, an information energy ratio of XOR gate composed of single-electron transistors is proposed at the mesoscopic scale, which can be used to quantify the exchange between the information and energy at XOR gates. Furthermore, the energy efficiency of the parity check circuit is proposed to analyze the energy consumption of digital signal processing systems. Compared with the energy efficiency of parity check circuit adopting the 7 nm semiconductor process supply voltage, simulation results show that the energy efficiency of the parity check circuit is improved by 266% when the supply voltage is chosen at a specified value.

Abstract: Isolated training with Gaussian priors (TGP) of the component autoencoders of turbo-autoencoder architectures enables faster, more consistent training and better generalization to arbitrary decoding iterations than training based on deep unfolding. We propose fitting the components via extrinsic information transfer (EXIT) charts to a desired behavior which enables scaling to larger message lengths ($k \approx 1000$) while retaining competitive performance. To the best of our knowledge, this is the first autoencoder that performs close to classical codes in this regime. Although the binary cross-entropy (BCE) loss function optimizes the bit error rate (BER) of the components, the design via EXIT charts enables to focus on the block error rate (BLER). In serially concatenated systems the component-wise TGP approach is well known for inner components with a fixed outer binary interface, e.g., a learned inner code or equalizer, with an outer binary error correcting code. In this paper we extend the component training to structures with an inner and outer autoencoder, where we propose a new 1-bit quantization strategy for the encoder outputs based on the underlying communication problem. Finally, we discuss the model complexity of the learned components during design time (training) and inference and show that the number of weights in the encoder can be reduced by 99.96 %.

Abstract: Channel estimation is always implemented in communication systems to overcome the effect of interference and noise. Especially, in wireless communications, this task is more challenging to improve system performance while saving resources. This paper focuses on investigating the impact of geometries of antenna arrays on the performance of structured channel estimation in massive MIMO-OFDM systems. We use Cram'er Rao Bound to analyze errors in two methods, i.e., training-based and semi-blind-based channel estimations. The simulation results show that the latter gets significantly better performance than the former. Besides, the system with Uniform Cylindrical Array outperforms the traditional Uniform Linear Array one in both estimation methods.

Abstract: As an evolving successor to the mobile Internet, the extended reality (XR) devices can generate a fully digital immersive environment similar to the real world, integrating integrating virtual and real-world elements. However, in addition to the difficulties encountered in traditional communications, there emerge a range of new challenges such as ultra-massive access, real-time synchronization as well as unprecedented amount of multi-modal data transmission and processing. To address these challenges, semantic communications might be harnessed in support of XR applications, whereas it lacks a practical and effective performance metric. For broadening a new path for evaluating semantic communications, in this paper, we construct a multi-user uplink non-orthogonal multiple access (NOMA) system to analyze its transmission performance by harnessing a novel metric called age of incorrect information (AoII). First, we derive the average semantic similarity of all the users based on DeepSC and obtain the closed-form expressions for the packets' age of information (AoI) relying on queue theory. Besides, we formulate a non-convex optimization problem for the proposed AoII which combines both error-and AoI-based performance under the constraints of semantic rate, transmit power and status update rate. Finally, in order to solve the problem, we apply an exact linear search based algorithm for finding the optimal policy. Simulation results show that the AoII metric can beneficially evaluate both the error- and AoI-based transmission performance simultaneously.

Abstract: Radio-frequency wireless energy transfer (WET) is a promising technology to realize wireless-powered underground sensor networks (WPUSNs) and enable sustainable underground monitoring. However, due to the severe attenuation in harsh underground soil and the tight energy budget of the underground sensors, traditional WPUSNs relying on the channel state information (CSI) are highly inefficient, especially in massive WET scenarios. To address this challenge, we comparatively assess the feasibility of several state-of-the-art CSI-free multi-antenna WET schemes for WPUSNs, under a given power budget. Moreover, to overcome the extremely low WET efficiency in underground channels, we propose a distributed CSI-free system, where multiple power beacons (PBs) simultaneously charge a large set of underground sensors without any CSI. We consider the position-aware K-Means and the position-agnostic equally-far-from-center (EFFC) approaches for the optimal deployment of the PBs. Our results evince that the performance of the proposed distributed CSI-free system can approach or even surpass that of a traditional full-CSI WET strategy, especially when adopting an appropriate CSI-free scheme, applying the advisable PBs deployment approach, and equipping the PBs with an appropriate number of antennas. Finally, we discuss the impact of underground parameters, i.e., the burial depth of devices and the volumetric water content of soil, on the system's performance, and identify potential challenges and research opportunities for practical distributed CSI-free WPUSNs deployment.

Abstract: Recent advances in machine learning-aided lossy compression are incorporating perceptual fidelity into the rate-distortion theory. In this paper, we study the rate-distortion-perception trade-off when the perceptual quality is measured by the total variation distance between the empirical and product distributions of the discrete memoryless source and its reconstruction. We consider the general setting, where two types of resources are available at both the encoder and decoder: a common side information sequence, correlated with the source sequence, and common randomness. We show that the region under the strong perceptual constraint is a subset of that for the weaker empirical perceptual constraint. When sufficient common randomness is provided, the required communication rate is the minimum conditional mutual information such that the distortion and perceptual constraints are satisfied. The coding scheme in the proof of achievability takes advantage of the likelihood encoder.

Abstract: Satellite communication constitutes a promising solution for the sixth generation (6G) wireless networks in terms of providing global communication services. In order to provide a cost-effective satellite network, we propose a novel medium-earth-orbit (MEO) satellite aided integrated-navigation-and-communication (INAC) network. To overcome the severe path loss of MEO satellites, we conceive a network for simultaneous serving navigation and communication for ground users by adopting the non-orthogonal multiple access (NOMA) technique and the reconfigurable intelligent surface technique. Based on the power allocation strategies, communication-oriented (CO-) and navigation-oriented (NO-) INAC scenarios are proposed. We first derive the closed-form expressions for the new channel statistics, outage probability and channel capacity of the INAC-user. For gleaning further insights, the diversity orders and navigation accuracy are evaluated for illustrating the performance of the INAC networks. According to our analysis, when RIS elements are sufficient, the proposed INAC network can perform better than conventional terrestrial communication networks in terms of channel capacity. Numerical results are provided for confirming that the NO-INAC and CO-INAC scenarios have superior performance for communication in the low signal-to-noise-ratio (SNR) regimes and high SNR regimes, respectively, which indicates a hybrid CO/NO-INAC network is preferable.

Abstract: This paper presents an achievability bound that evaluates the exact probability of error of an ensemble of random codes that are decoded by a minimum distance decoder. Compared to the state-of-the-art which demands exponential computation time, this bound is evaluated in polynomial time. This improvement in complexity is also attainable for the original random coding bound that utilizes an information density decoder. The general bound is particularized for the binary symmetric channel, the binary erasure channel, and the Gaussian channel.

Abstract: A framework for the analysis of synchronous grant-free massive multiple access schemes based on the irregular repetition slotted ALOHA (IRSA) protocol and operating over the Gaussian multiple access channel is presented. IRSA-based schemes are considered here as an instance of the class of unsourced slotted random access codes, operating over a frame partitioned in time slots, and are obtained by concatenation of a medium access control layer code over the entire frame and a physical layer code over each slot. In this framework, an asymptotic analysis is carried out in presence of both collisions and slot decoding errors due to channel noise, which allows the derivation of density-evolution equations, asymptotic limits for minimum packet loss probability and average load threshold, and a converse bound for threshold values. This analysis is exploited as a tool for the evaluation of performance limits in terms of minimum signal-to-noise ratio required to achieve a given packet loss probability, and also provides convergence boundary limits that hold for any IRSA scheme with given physical layer coding scheme. The tradeoff between energy efficiency and spectrum efficiency is numerically evaluated comparing some known coding options, including those achieving random coding bounds at slot level. It is shown that IRSA-based schemes have a convergence boundary limit within few dB from the random coding bound when the number of active transmitters is sufficiently large.

Abstract: In this letter, we study the performance of a single-user fluid antenna system (FAS) under arbitrary fading distributions, in which the fading channel coefficients over the ports are correlated. We adopt copula theory to model the structure of dependency between fading coefficients. Specifically, we first derive an exact closed-from expression for the outage probability in the most general case, i.e., for any arbitrary choice of fading distribution and copula. Afterwards, for an important specific case, we analyze the performance of the outage probability under correlated Nakagami-$m$ fading channels by exploiting popular Archimedean copulas, namely, Frank, Clayton, and Gumbel. The results demonstrate that FAS outperforms the conventional single fixed-antenna system in terms of the outage probability. We also see that the spatial correlation dependency structure for the FAS is a key factor to determine its performance, which is natively captured through the choice of copula.