ALT We study the thermodynamic efficiency of message-passing decoders using the mismatch cost framework. This framework quantifies the excess entropy generated when a system operates away from the thermodynamically optimal initial distribution. It provides a computable lower bound on irrecoverable energy loss. The decoder is modeled as a main decoding program with local message updates implemented as subroutines. Memory is treated as an external copying subsystem whose thermodynamic cost is excluded. Studying the [7,4] Hamming code transmitted over a binary erasure channel, we show how the channel-induced initialization statistics and the step-wise evolution of the algorithmic state distribution during decoding determine the total mismatch cost. We further show that different thermodynamically optimal state distributions, representing different underlying physical implementations of the decoder, can produce different thermodynamic costs for identical decoding dynamics. Conditioning the inp

ALT For any desired rate R ∈ (0,1), and gap to list-decoding capacity ε > 0, we give an explicit nᴼε⁽¹) time construction of Reed-Solomon codes over extension fields of size polynomial in the block length n that can be list-decoded from a fraction 1-R-ε of errors with the optimal list-size of O(1-R/ε). We also give a simpler, strongly explicit construction of evaluation points for which the associated Reed-Solomon code can be list-decoded from 1-R-ε errors with list size (1/ε)ᴼ⁽¹/ε). We provide a deterministic list-decoding algorithm for both constructions running in time Oε(1)poly(n). In fact, our Reed-Solomon codes are near-optimal subspace-design codes over a subfield. Via known results, this directly implies the combinatorial list-decoding guarantee, as well as near-optimal list-recovery bounds. We also present a new reduction showing that the subspace-design guarantee also implies line decoding over the extension field itself, which then yields proximity gaps and mutual correlated agr

ALT Accurate CSI forecasting is essential for mitigating channel aging and supporting reliable downlink transmission in high-mobility wireless systems. In FDD systems, forecasting future DL CSI from historical UL observations requires joint temporal extrapolation and cross-band inference. However, defining historical UL as the input and future DL as the target does not specify how elapsed time and UL-to-DL band separation should be represented in a pretrained predictor's positional space. FAR-CSI establishes an FDD-aware representation of channel forecasting within a joint temporal and operating-band positional field. Within this field, historical UL observations and future DL targets occupy segregated regions according to their temporal and operating-band roles, preserving the distinction between observed UL context and unobserved DL prediction targets. This representation is instantiated through a unified structured routing rule that governs encoder positional assignment, decoder-field r

ALT We study deterministic causal quantization with pathwise error at most ε, using ω shared representatives updated from transmitted addresses alone. For a midpoint realization with first-in, first-out replacement, we compare address entropy rates with process ε-entropy, the least entropy rate of any block quantizer meeting the same constraint. From ε-separated initialization, the gap is at most two bits per sample for every stationary source with finite scalar ε-entropy, without density, independence or mixing assumptions. A causal address-tree argument extends this comparison to any synchronized quantizer with cell overlap m, giving log₂ m bits. Lattice initialization with consistent boundary ownership realizes uniform grids with sharp one-bit scalar and process comparisons. Under an entropy condition and finite Fisher information rate J, the gap is at most 2Jε²/(π²ln 2); general initializations add a term of order ωε√J. The scalar grid estimate gives a nonasymptotic form of Rényi's the

ALT In federated learning (FL), secure aggregation enables a server to compute the sum of local model updates of N clients, without revealing any information on the individual model updates to the server, beyond their sum. Different clients may be subject to heterogeneous bandwidth constraints, and consequently may choose different numbers of quantization levels to represent the information they send. Most secure aggregation works require the clients to project the values of their update parameters to a common finite group (or field), which does not directly accommodate heterogeneous precision constraints on their transmitted masked updates. Existing approaches of secure aggregation with heterogeneous quantization levels reveal partial aggregates of model-updates, and can reveal segments of individual model updates, under certain dropout and client-server collusion patterns. To prevent this privacy breach, we propose an information-theoretic secure aggregation scheme that tolerates client

ALT Dynamic metasurface antennas (DMAs) have emerged as a promising technology for realizing large-scale antenna arrays in next-generation wireless networks owing to their ability to enable dense and energy-efficient antenna architectures. However, jointly optimizing digital beamforming and DMA element weights under time-varying channel conditions remains challenging due to their coupled effects on the received signal and interference powers. We formulate this problem to maximize time-averaged energy efficiency (EE) under time-varying channel conditions, subject to transmit power constraints, Lorentzian phase limitations, and minimum rate requirements. To enable long-term planning and improve sample efficiency compared with model-free reinforcement learning, we develop a world model framework that learns latent system dynamics from interactions with the environment and jointly optimizes digital beamforming and DMA element weights through imagined trajectories. Furthermore, we incorporate f

ALT Minimal binary linear codes play an important role in secret-sharing schemes and in the structural study of linear codes. We study the minimality of three classes of known constructions: codes from a single complete Hamming-weight layer, codes from arbitrary unions of such layers and graph cut-space codes. For the previously studied single-layer codes C, we give a complete minimality classification: C is minimal if and only if t is even. For t = 4, we determine the minimum and maximum weights, and show that the family strictly violates the binary Ashikhmin Barg sufficient condition for every k. We also calculate the minimum distance of the dual code. For arbitrary unions of complete Hamming-weight layers, we obtain an if-and-only-if classification of minimality and uniform criteria for evenness, self-orthogonality, the doubly even property and hull dimension. We further analyze the family for odd k. Finally, using the classical bond characterization of cuts, we translate minimality of

ALT In this paper, we investigate a family of trace codes over finite fields of odd characteristic defined by two quadratic trace conditions. By analyzing the quadratic forms associated with these trace conditions and evaluating the corresponding character sums, we obtain the parameters and complete weight distributions of the codes. We further exploit the natural multiplicative orbit structure of the defining sets to obtain punctured codes and determine their parameters, weight distributions and dual distances. Moreover, we establish self?orthogonality criteria and investigate divisibility and projectivity of the constructed codes. These results give a unified treatment for arbitrary odd prime fields and for extension degrees of both parities.

ALT Additive codes generalize linear codes and play an important role in the construc?tion of quantum codes. As generalizations of linear MDS codes, additive MDS codes have received much research attention. As an important subclass of additive codes, ACD codes are widely used for quantum error correction. In this paper, we study single-twist additive generalized twisted Reed-Solomon (GTRS) codes over finite fields. We derive necessary and sufficient conditions for these codes to be MDS for arbitrary hook and twist parameters. Then we employ Schur squares to prove that such additive MDS codes are not monomially equivalent to additive Reed-Solomon codes. We also identify a class of additive GTRS codes whose duals remain additive GTRS codes, and show that, for all sufficiently large prime powers q whose characteristic avoids a finite set, such GTRS codes yield ACD codes.

ALT Mass formulas for prescribed hull dimensions have mainly been studied for linear codes viewed as subspaces of the whole space. We study internal enumeration for an arbitrary fixed parent code. Let C be an [n,k]q linear code with an ℓ-dimensional hull, and let s be the subcode dimension. We determine the number of subcodes with prescribed dimension, hull dimension, and type over finite fields of both even and odd characteristic. We decompose the parent code into an LCD complement and its hull, and use projection to reduce enumeration to the corresponding problem inside the LCD complement. This yields explicit formulas refined by complete type and shows that the counts depend only on the relevant parameters, not on the particular parent code or its length. The known whole-space mass formulas and the enumeration of LCD subcodes of LCD codes arise as special cases. Motivated by code extension, we also study the dual containment problem: for a fixed code, we enumerate larger codes containin

ALT Secure convertible codes, introduced by Zhang and Rashmi, achieve secrecy capacity under a passive eavesdropper model in which an eavesdropper is allowed to access any ℓ symbols from the initial and final codewords. In this paper, we construct two families of access-optimal secure convertible codes. The first family of codes based on Maximum Rank Distance (MRD) codes is constructed for all parameters in the merge and split regimes and requires a large field size. The second family of codes, constructed using Generalized Reed-Solomon codes, uses smaller fields but is applicable only for certain parameters in the merge and split regimes.

ALT Every perfect r-error-correcting Lee code in ℤⁿ induces a finite configuration around each codeword: a family of pairwise disjoint radius-r Lee spheres, all disjoint from the central sphere, that covers every lattice point at Lee distance r+1 from the codeword. We call such a configuration a complete covering. Under projection onto a suitable Cartesian product of cycles, a complete covering corresponds to an optimal local structure in the sense of Špacapan. The existence of a complete covering is necessary but, in general, not sufficient for the existence of a perfect Lee code, as our construction for (n,r)=(3,2) shows. We prove that no complete covering exists whenever n≥ 8 and r²+⌊25r/34⌋-3≥ 2n. For the corresponding Cartesian products of cycles, this strengthens Špacapan's nonexistence theorem by replacing the linear radius condition r≥ n with a threshold of order √(2n). We also obtain an improved large-radius nonexistence bound for perfect Lee codes, strengthening the bound of Hora

ALT The canonical ℤ₂ˢ-linear Hadamard codes are the Gray images of the ℤ₂ˢ-additive codes. Their rank, the dimension of the binary linear span, was known in closed form only for s≤ 3, and for s ≥ 4 only through computer computations for small lengths. We give a method that computes the rank for every s. We show that the rank is a binomial polynomial in the type parameters, with coefficients ρₛ(boldsymbolk) independent of the length. We compute all the coefficients for s≤ 5, which yields explicit rank formulas over ℤ₄ and ℤ₈ (recovering the known ones), and over ℤ₁₆ and ℤ₃₂.

ALT Semantic error control coding (SECC) has emerged as a promising paradigm for improving communication reliability by exploiting the inherent structure and semantic dependencies of transmitted information. This paper proposes a semantic successive cancellation list (SCL) decoder for polar codes carrying natural-language text. A fine-tuned byte-level language model provides next-byte priors, which are converted into conditional bit costs and incorporated directly into the SCL path metric before each pruning step. This allows the decoder to jointly exploit channel reliability and source structure while retaining the conventional polar coding framework. The language model can also be invoked only for bytes whose channel decisions are unreliable, trading decoding performance for latency. Simulations for length-512 polar codes show substantial block error rate (BLER) improvements over conventional CRC-aided SCL (CA-SCL) decoding. At rate R=0.75 and list size L=16, the proposed decoder achieve

ALT Generative lossy compression combines a rate-limited representation with a stochastic decoder that preserves source-dependent information while generating unresolved detail. We ask what remains reusable when a rate-distortion-perception (RDP) system selected for one operating point is transferred to a prescribed conditional-generation task. We distinguish the single-letter RDP factorization from its block-code implementation and compare Full Redesign with three increasingly restrictive transfer strategies. Renderer-Only Transfer retains only the renderer and redesigns semantic steering. Representation-Induced Transfer additionally retains the semantic latent law induced by the original representation. Full-Model Transfer retains a compatible RDP code, marginalizing over the task conditional law to form its semantic encoder. For finite alphabets, we characterize Renderer-Only Transfer's exact compression-common-randomness rate region, renderer-hull controllability condition, and compres

ALT Semantic communication is emerging as a pivotal paradigm to overcome wireless resource scarcity in 6G networks. This paper proposes a novel end-to-end framework for semantics-aware resource allocation in multi-user Edge AI. We extend the Opportunistic Information Bottleneck (OIB) to a multi-view setting, termed the Multi-view Gaussian Information Bottleneck (MGIB), by fusing complementary source views without variational approximation or network retraining. A resource allocation framework is then formulated for joint compression-level selection, transmission mode selection (i.e., the number of active sources per group), and PRB assignment. The problem is formulated as a Mixed-Integer Linear Program (MILP), solved efficiently via a proposed Lagrangian Relaxation (LR) algorithm, and benchmarked against the NP-hard optimal solution. Simulations demonstrate that the proposed LR scheme achieves near-optimal utility, and doubles PRB efficiency versus average allocation.

ALT In this paper, we focus on decoding MDS linear block codes for insdel errors. Building on our recent work for two-dimensional Reed-Solomon codes, we present a decoding algorithm for bounded distance decoding for the general insertion-and-deletion scenario that can be used for any MDS code of rate at most half. Our algorithm employs a sliding window and has a time complexity smaller than brute-force decoding. In particular, for optimal Reed-Solomon codes, it corrects insdel errors up to the half-Singleton bound, which exceeds the scope of existing methods. Additionally, for the special cases of insertion-only and deletion-only insdel error patterns, we present two different algorithms with a time complexity smaller than our general algorithm.

ALT This paper develops a channel model for scattering from a broad class of integrated sensing and communication (ISAC) targets-robots, humans, and automobiles-based on a unified measurement campaign at 28 GHz. Nine targets are characterized from numerous transmitter–receiver configurations per target, spanning full bistatic and aspect angles and thus covering backward to forward scattering. Repeated acquisitions are collected for each configuration to capture target motion and dynamics, yielding nearly 117 000 acquisitions in total. Measurements are collected with a 2 GHz-wide channel sounder equipped with a 256-element phased-array antenna, followed by digital beamforming and super-resolution processing for reliable extraction of multiple paths in delay and 2D angle, with average estimation errors of 0.1 ns and 0.2° respectively. From these measurements, we reduce a path-specific channel representation in which the scattering is modeled as a cluster of paths whose center is defined by t

ALT We study the minimum extension degree required for a Reed–Solomon code to admit exact Fq-linear repair at the cut-set bound from every prescribed set of d helpers. Let s=d-k+1, and let Qₛ(n) be the minimum product of n pairwise coprime integers, each at least s. For every prime power q and all 3≤ k<d<n≤2d-2, we prove that the minimum degree over Fq is exactly sQₛ(n). When all surviving nodes are helpers, we also characterize the admissible extension degrees and bound the number of coordinates that can attain the cut-set bound. The required achievability follows from existing construction methods; we give a short existence proof using splitting subspaces. For a family of parameters with n>2d-2, we obtain strictly smaller extension degrees, showing that the range restriction cannot be omitted altogether. Finally, we prove that a nonlinear repair scheme attaining the cut-set bound induces an Fₚ-linear repair scheme on the same code, where p is the characteristic. Consequently, the extensi

ALT Fluid antenna arrays (FAAs) reconfigure their effective aperture by activating radiation ports from a dense set of candidate positions within a finite physical region, thereby offering geometry diversity beyond conventional fixed arrays. This paper studies arbitrary-direction far-field beam synthesis with a planar FAA. Since a fixed array adapts its beamforming weights on a predetermined spatial sampling structure, its ability to match desired beam patterns is limited when both the aperture and the number of active elements are constrained. To exploit the geometry diversity of the FAA, we propose a coarse-to-fine scheme that couples discrete port selection with continuous joint refinement. In the coarse stage, a fast Fourier transform (FFT) based phase retrieval step converts the amplitude-only beam specification into an aperture-compatible complex target, after which an FFT-tailored greedy method selects the active ports and least squares initializes their complex weights. In the fine