The paper is devoted to the task of ensuring strict requirements for latency and reliability of data delivery for uplink video traffic generated by a remote vehicle control application in 5G Vehicle-to-Everything (V2X) networks. A distinctive feature of this type of traffic is that the size of video frames is variable, so we propose using a hybrid radio resource allocation scheme. According to this scheme, each user is assigned a dedicated subchannel, as well as a subchannel common to all users, which is used when the resources of the dedicated subchannel are insufficient to transmit a packet. We develop an analytical model that allows us to estimate the probability of packet loss for each user when using a hybrid resource allocation scheme. We show how to select optimal parameters for the hybrid scheme by using the developed analytical model.

Abstract Wi-Fi standardization continues: IEEE 802.11bn (Wi-Fi 8) reached Draft 1.0 in August 2025 and is progressing through comment resolution. The wireless industry now stands at a pivotal crossroads as it begins to define Wi-Fi 9. This paper analyzes technical directions and candidate features for the post-802.11bn amendment, tentatively referred to as Wi-Fi 9. We synthesize contributions from device manufacturers, network operators, and research institutions presented to the IEEE 802.11 Wireless Next Generation Standing Committee in early 2026. The emerging consensus indicates that, rather than increasing the nominal data rates, the next generation will likely prioritize deterministic performance, reliability, and expanded application domains. The paper examines the market forces driving this transition, including AI workloads that invert traditional traffic asymmetry, industrial robotics that demand sub-millisecond latency, and immersive entertainment that requires the simultaneous satisfaction of throughput, latency, and reliability constraints. Then the paper analyzes candidate technologies spanning PHY and MAC layer transformations, coordination between multiple networks, and AI integration throughout the protocol stack. Implementation challenges, including backward compatibility tradeoffs and spectrum availability, are discussed. Finally, the paper outlines the anticipated standardization timeline targeting commercial deployment of Wi-Fi 9 in the 2030s.

We propose an analytical representation of complexity diagrams based on information about the number of discretes in the signal spectrum and the signal-to-noise ratio. This approach provides additional criteria for solving the classification problem. We formulate and prove lemmas on the construction of analytical metric grids for complexity diagrams. The obtained results are verified by numerical experiments, which have confirmed the efficiency of these methods.

In a number of LoRaWAN sensor network scenarios, it is required to deliver data with a given reliability and with minimal sensor energy consumption. To improve the reliability of data delivery in a LoRaWAN network, data can be transmitted in two modes: (i) with acknowledgments and retries of undelivered data, or (ii) without acknowledgments and with unconditional retries. In this paper, we develop a model of a LoRaWAN network in which some devices transmit data in the first mode and some in the second mode. The model makes it possible to find the dependence of packet loss probability, sensor energy consumption, and base station duty cycle on the traffic intensity. Based on the modeling results, we propose an algorithm for selecting the fraction of sensors transmitting data with confirmation and the number of repetitions for sensors transmitting data with unconditional repetitions that minimizes energy consumption, fulfills the limit on the duty cycle, and ensures the desired reliability of data transmission.

Nowadays, the Hough transform (HT) is a tool extensively used in image processing and computer vision. It finds applications ranging from line detection in images to tomographic reconstruction. Due to their numerous industrial applications, which comprise execution not only on remote servers but also on less powerful embedded devices and within the Internet of Things (IoT) paradigm, fast algorithms for computing the HT (fast HT, or FHT) that efficiently utilize computational memory are in high demand. In-place algorithms, which use memory allocated for the input data array and may employ a small amount of additional memory for intermediate calculations, are recognized to have such characteristics. For images with widths that are powers of two, such an algorithm is known; it is the in-place version of the de facto standard Brady–Yong algorithm. However, in practice, it is often needed to compute the FHT for images with arbitrary widths, to which the Brady–Yong algorithm is not applicable. In this paper, we propose an in-place $\mathit{FHT}2\mathit{IDS}$ algorithm. It is a modification of the $\mathit{FHT}2\mathit{DS}$ out-of-place algorithm for computing the FHT for images of arbitrary width previously presented in the literature. We justify correctness of the $\mathit{FHT}2\mathit{IDS}$ algorithm and show that the result of processing an image of an arbitrary width matches the output of the $\mathit{FHT}2\mathit{DS}$ algorithm. We demonstrate that the $\mathit{FHT}2\mathit{IDS}$ algorithm allocates a significantly smaller data array at each recursion step compared to the $\mathit{FHT}2\mathit{DS}$ algorithm: at each recursion step, it requires an array of size no greater than $w+h$ , rather than $wh$ , assuming that the input image has a $w\times h$ shape. We also develop a nonrecursive version of the $\mathit{FHT}2\mathit{IDS}$ algorithm, which is called the $\mathit{FHT}2\mathit{IDS}$ - $\mathit{NonRecursive}$ algorithm. The auxiliary space complexity of the $\mathit{FHT}2\mathit{IDS}$ - $\mathit{NonRecursive}$ algorithm is proved to be $\mathcal{O}(w+h)$ , while the $\mathit{FHT}2\mathit{DS}$ - $\mathit{NonRecursive}$ algorithm, a nonrecursive version of the $\mathit{FHT}2\mathit{DS}$ algorithm, demonstrates the auxiliary space complexity of $\mathcal{O}(wh)$ , where $w$ and $h$ denote the dimensions of the input image. Experimental results show that the $\mathit{FHT}2\mathit{IDS}$ - $\mathit{NonRecursive}$ algorithm implemented in C/C $\texttt{++}$ is 45% faster than its out-of-place counterpart, $\mathit{FHT}2\mathit{DS}$ - $\mathit{NonRecursive}$ . The $\mathit{FHT}2\mathit{IDS}$ and $\mathit{FHT}2\mathit{IDS}$ - $\mathit{NonRecursive}$ algorithms are also implemented in Python within an open-access adrt library, which the readers may find useful in their research.

This paper introduces a novel method for transposing summing algorithms, which eliminates the need for an explicit matrix representation of a direct summing operator. Unlike the approach previously proposed in the literature, which relies on decomposing the direct operator matrix into simpler factors, our method leverages a graph-based interpretation using directed acyclic graphs (DAGs). By focusing on the analysis of structure of the DAG associated with the summing algorithm, we avoid the complex and often cumbersome task of operator matrix factorization. The proposed method maintains the asymptotic computational efficiency of the original algorithm while offering a more accessible and flexible framework for transposition. In this paper, capabilities of graph interpretation are demonstrated by analyzing fast algorithms for computing forward and backward projection operators for a 2D low-angle reconstruction problem for circular-orbit parallel-beam CT. As a key component, these algorithms incorporate the transposition of classical fast Hough transform (HT) operators, including that realized by the Brady–Yong algorithm. Moreover, we apply the proposed transposition method to the novel $\mathit{FHT}2\mathit{DT}$ algorithm for fast and substantially accurate computation of the HT. The transposed $\mathit{revFHT}2\mathit{DT}$ algorithm offers a computationally efficient approach for calculating the transposed HT for images of arbitrary size. This overcomes the limitations of the transposed Brady–Yong algorithm, which is restricted to images with power-of-two widths.

We prove the universality of the regular realizability problem for several classes of filters. These filters are descriptions of finite relations on the set of nonnegative integers in the format proposed by P. Wolf and H. Fernau. The universality is proved with respect to the disjunctive reduction in polynomial time for unary relations and in polynomial space for invariant binary relations. The necessity of stronger reductions corresponds to the results of Wolf and Fernau on the decidability of regular realizability problems for many algorithmic problems in graph theory.

We propose several constructions of nonbinary constant-weight codes meeting the Johnson bound.

A key problem of low-density parity-check (LDPC) codes analysis is estimation of an extremely low error floor that occurs at a high level of the signal-to-noise ratio (SNR). The importance sampling (IS) method is a popular approach to address this problem. Existing works typically use a normal sampling probability density function (PDF) with shifted mean, which yields a large variance of the estimate. In contrast, uniform distribution has equally probable samples on the entire range and thus should reduce the variance, but results in a biased estimation. This paper proposes a modified IS approach (IS-U) that allows considering the uniform distribution as a sampling PDF, and shows that this estimation is better than the traditional one. Also, this paper demonstrates that the existing criteria cannot be applied to evaluate the accuracy of the IS-U on the whole SNR range. To address this issue, a new metric is proposed, which uses only the convergence rate and does not depend on the true data.

Using a concatenated construction for $$q$$ -ary codes, we construct codes over $$\mathbb{Z}_q$$ in the Lee metrics which after a proper mapping to the binary alphabet (which in the case of $$\mathbb{Z}_4$$ is the well-known Gray map) become binary Hadamard codes (in particular, Hadamard matrices). Our construction allows to increase the rank and the kernel dimension of the resulting Hadamard code. Using computer search, we construct new nonequivalent Hadamard matrices of orders $$32$$ , $$48$$ , and $$64$$ with various fixed values of the rank and the kernel dimension in the range of possible values. It was found that in a special case, our construction coincides with the Kronecker (or Sylvester) construction and can be regarded as a version of a presently known [1] modified Sylvester construction which uses one Hadamard matrix of order $$m$$ and $$m$$ (not necessarily distinct) Hadamard matrices of order $$k$$ . We generalize this modified construction by proposing a more general Sylvester-type construction based on two families of (not necessarily distinct) Hadamard matrices, namely, on $$k$$ matrices of order $$m$$ and $$m$$ matrices of order $$k$$ . The resulting matrix is of order $$mk$$ , as in the construction from [1].