In briefRow-weight limits on redundant checks for peeling decoding of random LDPC codes
SummaryThe paper studies peeling decoding on the binary erasure channel when redundant parity checks can be added freely but each check has a bounded row weight. For random simple binary regular LDPC codes, it considers the parity-check matrix formed by all nonzero dual codewords up to a given weight. Within an explicit logarithmic row-weight range, this full family of redundant checks has the same asymptotic normalized-residual threshold as peeling with the original LDPC matrix.
WhyProves that all low-weight redundant checks preserve the asymptotic peeling threshold of random regular LDPC codes in a logarithmic weight range, establishing a row-weight limitation with rigorous the
In briefFitting Fluid Antenna Channels with Extreme Value Distributions for Accurate Outage Evaluation
SummaryThis paper proposes a channel fitting strategy for single-antenna fluid antenna systems (FAS) that focuses on accurately evaluating outage probability (OP). It introduces a combined extreme value distribution (CEVD), using a generalized Pareto distribution for the left tail and a generalized extreme value distribution for global behavior. A modified mean-square-error criterion with logarithmic-domain errors and uniform sampling on the log CDF is developed to emphasize tail accuracy. Simulations show improved OP evaluation accuracy in the ultra-low-OP regime.
In briefTighter Upper Bound on the Ingleton Score for Four Random Variables
SummaryThis paper studies four finite discrete random variables and shows that the negative Ingleton expression divided by joint entropy is at most 19/124 (about 0.15323). This improves the previously reported bound of 3/19 by 11/2356. The proof uses a copy program with four copy steps and six auxiliary variables, verified by exact rational linear-programming certificates. The authors also show that two published inequalities imply the bound 5/32.
In briefSecure multi-access coded caching via a lifting transformation
SummaryThe paper builds secure cyclic multi-access coded caching schemes by re-encoding the caches of a secure single-access scheme while reusing its multicast message. Each user reads L consecutive shared caches, recovers its requested file, and learns nothing about other files. Deterministic Pascal-window and randomized complement-dual encoders are given, attaining exact minimum per-block storage over a suitable finite field. The resulting memory-rate family has approximation guarantees against converse bounds, and the L=K-1 tradeoff is proved exactly.
In briefHiNa-MoE: Fast, Non-Intrusive MoE Inference on CPUs with Matrix Engines
SummaryThis paper presents HiNa-MoE, an operator library that speeds up Mixture-of-Experts model inference on Intel AMX-equipped CPUs. It keeps expert weights in standard layouts, uses a simple page-interleaved policy for NUMA-aware work partitioning, and converts decode-phase matrix-vector operations into small matrix-matrix operations. The authors report speedups of up to 3.37x for FFN kernels and up to 2.09x for end-to-end inference over baselines, and state that it works plug-and-play with existing frameworks.
In briefCommuteProp: Decoupled Training for Communication-Bound Split LLM Fine-Tuning
SummaryThis paper addresses inefficiency in privacy-preserving split-learning fine-tuning of large language models, where clients sit idle waiting for server-side gradients. It proposes CommuteProp, an asynchronous algorithm that splits training into two concurrent phases, a cross-block forward-backward pass and an in-block weight update, so computation overlaps with communication. The authors provide asynchronous error and convergence analysis and derive an NS preconditioner to reduce staleness-induced noise. Experiments report substantial throughput gains with accuracy comparable to synchronous methods, and the method can be plugged into existing privacy-enhancement techniques.
In briefSecure device-to-device coded caching with limited-radius connections using lifting
SummaryThis paper studies secure coded caching in a device-to-device network where users on a cycle can only communicate with nearby users within a fixed radius. Each user must generate delivery signals from its cache and recover its requested file without learning any other file. The authors construct such schemes using an outer secret-sharing code and a secure local caching scheme, and they prove information-theoretic secrecy along with converse bounds on peak sum load. Within certain memory ranges, the schemes achieve optimal load or a constant-factor approximation.
In briefYou Only Convert Twice: Ozaki Scheme II for Repeated Tensor Mode Products
SummaryThis paper proposes OzII-RescaleBE, which keeps intermediate tensors in residue form during chained tensor mode products in Ozaki scheme II. Inputs are converted to residues only once at the start and reconstructed only at the end, with an implementation on INT8 Tensor Cores using CuTe DSL. Across three datasets and chain depths 3 to 7, normwise relative errors stay near 1e-16 to 1e-15, but rise to about 1e-13 at depth 8. Throughput and memory use are compared against two GEMMul8 baselines, with gains at smaller mode sizes and a slight deficit at size 256.
In briefNear-optimal coded caching that keeps both files and user demands private
SummaryThis paper studies coded caching where both file contents and user requests stay private: each user gets only its requested file and learns nothing about other files or other users' requests. The authors propose a scheme whose worst-case delivery rate is at most 9/2 times optimal, for all user and file counts and feasible cache sizes. They also derive lower bounds on delivery rate and exact results at minimal memory and unit delivery rate.
WhyGives near-optimal coded caching under joint file and demand privacy, with entropy-based lower bounds matching up to constants, a substantial theoretical advance.
In briefOptimal colorings in unweighted Max-k-Cut games can still be unstable to group deviations
SummaryThis paper studies Max-k-Cut games on unweighted graphs, where optimal colorings maximize social welfare. The authors disprove a conjecture by showing that for every k≥3 there is a finite, simple, connected graph with an optimal coloring that is not a strong equilibrium. A coalition can profitably deviate to another optimal coloring, benefiting all its members while outside players lose and social welfare is unchanged. The paper also gives an exact identity linking coalition gains, cut changes and internal conflicts, and bounds monochromatic edges remaining after strong deviations from general Nash equilibria.
In briefScalable distortion-aware clustering for fronthaul-limited cell-free MIMO networks
SummaryThis paper studies how to group access points in uplink cell-free MIMO networks with fronthaul limits, using maximum ratio combining. The optimization depends only on large-scale fading coefficients, and asymptotic analysis gives deterministic equivalent expressions for average network sum rate that account for quantization distortion. The authors exploit the structure of the resulting quadratic-over-linear objective to develop a polynomial-time scheme that reaches the global optimum. Numerical results show gains over improved existing methods and competitive performance against an exhaustive-search global optimum based on small-scale fading.
In briefFormalizing Microwave Analog Computing in Lean
SummaryThis paper takes a first step toward formalizing microwave analog computing in Lean, a proof assistant. Microwave signals can perform linear transformations directly as they propagate through a network. The authors formalize components such as hybrid couplers and phase shifters, their series and parallel connections, and the networks they form. They formally prove a necessary and sufficient condition for the transformations these networks can compute, and that the discrete Fourier transform of any power-of-two size is implementable. All proofs are checked by the Lean kernel, and the code is publicly available.
In briefA unified framework linking sensing, computation, and communication in over-the-air federated learning
SummaryThis paper addresses the fact that federated learning training data must first be collected by heterogeneous edge sensors, and that collection quality and cost affect learning performance. It models sensing noise, energy consumption, latency, and over-the-air aggregation distortion in an OTA federated learning system, and derives a non-convex convergence bound. Based on this, the authors formulate a per-round optimization balancing energy, latency, and learning quality, solved with an alternating procedure. Numerical experiments show the benefit of jointly optimizing sensing, computation, and communication decisions.
Mehdi Karbalayghareh, David J. Love, and Christopher G. Brinton
In briefFluid antenna secure channel-driven constellation: a physical-layer security method for hiding data in channel points
SummaryThis paper proposes the FASCC framework for downlink communication, where information is carried by constellation points formed through fluid antenna port selection and phase adaptation. Two complementary schemes are developed depending on whether the eavesdropper's channel state information is available. Numerical results show significant secrecy gains in bit error rate and mutual-information secrecy, even when the eavesdropper is much closer to the base station than the legitimate user.
In briefApproximate feedback Nash equilibria in constrained games via model predictive control with a provable error bound
SummaryThis paper proposes a model predictive control method that approximates feedback Nash equilibrium trajectories in differential games by repeatedly solving finite-horizon open-loop games. An auxiliary-game formulation selects prediction horizons and terminal costs, and hard constraints are incorporated through a constrained open-loop game. For the unconstrained case, the authors derive an analytic upper bound on the state-trajectory deviation from the true equilibrium, and they compare the method numerically with baseline approaches.
