VTC 2025 Spring Conference’s Shorts

Efficient Multi-RIS enabled Beam Routing in THz Systems for 6G Wireless Networks

Reconfigurable intelligent surfaces (RISs) hold great potential for addressing the challenges in terahertz (THz) communication. However, a single RIS cannot sufficiently overcome the high path loss of THz frequencies. This paper proposes a beam routing scheme for multi-RIS-assisted sixth-generation (6G) networks, employing a dynamic programming algorithm to optimize the propagation environment through multiple RISs for efficient multi-hop communication. A closed-form expression for ergodic capacity is derived. Simulation results demonstrate significant enhancements in throughput and reliability, highlighting the advantages of this approach over traditional methods and supporting the deployment of THz networks for future wireless applications.Efficient Multi-RIS enabled Beam Routing in THz Systems for 6G Wireless NetworksRithwik Premanand, Narendra Vishwakarma, Ashutosh Anshul, Ranjan Singh, Nanyang Technological University, Singapore; A.S. Madhukumar, Nanyang Technological University

Efficient Minimum Finders for Wi-Fi 7 Dimension Reduction Soft Demodulator

In this paper, we propose efficient minimum finders for dimension reduction soft demodulators (DRSD) of Wi-Fi 7 modems with 2x2 MIMO. Minimum finder hardware architectures of DRSD can consists of multiple tree based minimum finders with multiplexers those select valid Euclidean distances (ED) of symbols for each bit value. Firstly, the proposed minimum finder separates quadrature amplitude modulation (QAM) into two pulse amplitude modulations (PAMs) by finding intermediate real and imaginary minimum EDs among EDs of symbols with the same real parts and those with the same imaginary parts respectively. Then, the minimum EDs for each bit value are found among the intermediate minimum EDs in the first step. The proposed minimum finder is efficient for symbols of all constellation points and reduced candidate symbols with determined shape. For symbols of all constellation points of 2m-QAM, the complexity of the number of minimum values is O(2m) compared with O(m·2m) of the conventional method. For reduced candidate symbols of 4096-QAM, we propose the initial candidate reduction (ICR) method using 5x5 square symbols and 6 mirror symbols for each spatial stream. The areas of the proposed minimum finder and previous minimum finders without using shapes are compared when synthesized with 4 nm CMOS technology for 480 MHz operation. The synthesized area of the proposed minimum finder is 35 % smaller than that of a previous minimum finder with shared minimum values.Efficient Minimum Finders for Wi-Fi 7 Dimension Reduction Soft DemodulatorSoonwoo Choi, Minki Ahn, Taeshin Park, Junyoung Jeong, Samsung Electronics

Efficient decoder-free minimum distance estimation for concatenated convolutional codes

This work presents a novel approach for estimating the minimum distance of concatenated convolutional codes. Unlike most prior methods, the proposed approach relies solely on encoder-side properties, eliminating the need for a decoder in the estimation process. To this end, we introduce an alternative method for identifying return-to-zero sequences, enabling a low-complexity, reliable minimum distance estimation. The proposed method is flexible and applicable to both serial and parallel concatenated structures. The results confirm that this approach produces exact minimum distance values for several sizes of the LTE turbo code family while significantly reducing processing time and computational complexity compared to existing methods. For example, in a challenging case study, applying the method to an LTE turbo code with tailbiting termination of length K = 6144 bits yields an estimated minimum distance of 50 and a multiplicity of 12288 in 100 minutes on a standard personal computer - a reduction by several orders of magnitude in comparison to state of the art methods.Efficient decoder-free minimum distance estimation for concatenated convolutional codesMohmmad Bazzal, IMT Atlantique; Jérémy NADAL, IMT-Atlantique; Stefan Weithoffer, Charbel Abdel Nour, Catherine Douillard, IMT Atlantique

Visual-Tactile Fusion for Multimodal Semantic Communication with Foundation Models

Integrating vision and touch is key to understanding the physical world, but it faces two main challenges: effective multimodal fusion and high-fidelity tactile representation. This paper proposes a multimodal semantic communication framework based on foundation models through visual-tactile fusion. First, a multimodal enhancement fusion network extracts deep features from video to improve tactile recognition and semantic understanding. Second, a CLIP-driven framework, grounded in a tactile knowledge base, enhances the accuracy of tactile information transmission. An end-to-end model with joint source-channel coding further improves transmission efficiency. Finally, we introduce a tactile generative reconstruction method using ImageBind, which ensures high similarity in both visual features and pressure distribution. Experimental results confirm the effectiveness of our approach in semantic tactile reconstruction. Overall, the proposed method enables efficient, low-bit-rate communication with high semantic fidelity, offering a promising solution for visual-tactile fusion in real-world applications.Visual-Tactile Fusion for Multimodal Semantic Communication with Foundation ModelsZhuorui Wang, Mingkai Chen, Nanjing University of Posts and Telecommunications; Xiaoming He, Nanjing University of Posts and Telefommunications; Haitao Zhao, Nanjing University of Posts and Telecommunications; Yun Lin, Harbin Engineering University; Mariam Hussain, National Defense University, NDU Islamabad; Shahid Mumtaz, Nottingham Trent University, NG1 4FQ Nottingham. U.K.

Low-Rate Semantic Communication with Codebook-based Conditional Generative Models

Generative semantic communication models are reshaping semantic communication frameworks by moving beyond pixel-wise optimization to align with human perception. However, many existing approaches prioritize image-level perceptual quality, often neglecting alignment with downstream tasks, which can lead to suboptimal semantic representation. This paper introduces an Ultra-Low Bitrate Semantic Communication (ULBSC) system that employs a conditional generative model and a learnable condition codebook. By integrating saliency conditions and image-level semantic information, the proposed method enables high-perceptual-quality and controllable task-oriented image transmission. Recognizing shared patterns among objects, we propose a codebook-assisted condition transmission method, integrated with joint source-channel coding (JSCC)-based text transmission to establish ULBSC. The codebook serves as a knowledge base, reducing communication costs to achieve ultra-low bitrate while enhancing robustness against noise and inaccuracies in saliency detection. Simulation results indicate that, under ultra-low bitrate conditions with an average compression ratio of 0.57‰, the proposed system delivers superior visual quality compared to traditional JSCC techniques and achieves higher saliency similarity between the generated and source images compared to state-of-the-art generative semantic communication methods.Low-Rate Semantic Communication with Codebook-based Conditional Generative ModelsKailang Ye, Mingze Gong, Shuoyao Wang, Daquan Feng, Shenzhen University

Diffusion Model-Enabled Intelligent Channel Denoising for UAV Semantic Communication

Semantic communication (SC), by compressing raw data at the semantic level, significantly improves the information entropy of transmitted data and is considered as one of the key enabling technologies for the next-generation communication. However, most current research underestimates the impact of channel interference on SC systems. As an innovative generative artificial intelligence technique, the diffusion model (DM) has demonstrated remarkable performance in image denoising and enhancement. In this paper, we focus on the effects of wireless channels on SC image transmission and propose an unmanned aerial vehicle (UAV)-enhanced SC framework, termed diffusion joint source-channel coding (D-JSCC). Initially, we deploy a ground-to-air SC system on UAVs, utilizing the aerial advantage to provide favorable channels. Subsequently, we employ DM for intelligent signal processing, adaptively denoising channel interferences and optimizing received images with respect to numerical errors and perceptual loss. The results show that D-JSCC consistently exhibits superior performance across various metrics over different channel conditions.Diffusion Model-Enabled Intelligent Channel Denoising for UAV Semantic CommunicationPengfei Ren, Jingjing Wang, Beihang University; Junhui Qian, Chongqing University; Jianrui Chen, Beihang University; Xin Zhang, Hong Kong University of Science and Technology; Chunxiao Jiang, Tsinghua University

Blind Adaptive Array Interference Suppression in LTE-WLAN Coexistence Environment

This paper investigates a potentiality of spectrum superposing in different systems through blind adaptive array (BAA) interference suppression. Various kinds of wireless communication systems are widely deployed such as LTE and Wireless LAN (WLAN). Mobile traffic is increasing due to services like video streaming on smartphones, leading to a shortage of spectrum resources in the microwave band. With the growing demand for wireless communication, efficient use of limited spectrum resources is required. In this paper, we conduct a link-level simulation of interference suppression of two orthogonal frequency division multiplexing (OFDM) based different systems, i.e. LTE and WLAN, using BAAs which does not require prior knowledge of interfering signals. We demonstrate that the spectrum efficiency can be improved by up to 53%.Blind Adaptive Array Interference Suppression in LTE-WLAN Coexistence EnvironmentTakeshi Kazama, Haruya Ikeda, Tokyo University of Science; Hideya So, Shonan Institute of Technology; Kazuki Maruta, Tokyo University of Science

A DL-Based Mutual Interference Suppression Approach for Uncoordinated Radar and Communicat...

The increasing demand for spectrum resources and their shortage make it inevitable for radar to share spectrum with communications, particularly for intelligent transportation systems (ITS). However, the coexistence of communication and radar leads to mutual interference, especially when the two systems are uncoordinated. Furthermore, complex and dynamic road environments limit the effectiveness of parameter estimation-based interference suppression methods. In this paper, we propose a deep learning (DL)-based interference suppression method, which can effectively suppress radar interference under uncoordinated scenarios. The received signal is first transformed into time-frequency domain by short-time Fourier transform (STFT). The magnitude of time-frequency representation is then fed into the network. After feature extraction and decoding, the estimated interference signal is obtained as the net output. The interference-free signal is subsequently reconstructed by subtracting the estimated interference from received signal. Simulation results validate the effectiveness of proposed algorithm.A DL-Based Mutual Interference Suppression Approach for Uncoordinated Radar and Communication Coexistence SystemTao Luo, Peng Chen, Mengyao Yang, Southeast University; Zhimin Chen, Shichen Jia, Shanghai Dianji University

Polarization Shift Keying Modulation for Backscatter Communications

Backscatter communication (BackCom) is a promising technology that enables ultra-low-power wireless communication by reflecting RF signals. We propose novel Binary polarization Shift Keying (BPolSK) and Differential polarization Shift Keying (DPolSK) in Bistatic BackCom. Here, the backscatter tag modulates the information by changing the polarization state of the incident RF carrier. We derive the closed-form expression for Bit Error Rate (BER) and analyze the performance of BPolSK and DPolSK. Our results compare the performance of BPolSK and DPolSK and verify that they can achieve low BER, demonstrating their reliability for BackCom applications.Polarization Shift Keying Modulation for Backscatter CommunicationsJiawang Zeng, Yimin Wang, UNSW; Deepak Mishra, University of New South Wales (UNSW) Sydney; Jinhong Yuan, University of New South Wales; A. Seneviratne, UNSW Sydney

Feedback-Aided Rateless Codes Unequal Error Protection for Multimodal Communication

In multimodal communication, the importance of different modalities varies due to factors such as the nonuniform distribution of information, differences in error tolerance, variations in information redundancy, network environment, and bandwidth limitations, as well as the synergistic effects between modalities. During transmission, due to network conditions and bandwidth constraints, it may not be possible to transmit the information of each modality to the receiver in an intact form to perform multimodal tasks. In response to the transmission characteristics and the unequal error protection requirements described above, this paper proposes an end-to-end multimodal rateless codes unequal error protection scheme from the perspective of logical links. We also introduced a feedback mechanism to implement algorithms such as adaptive code length adjustment, adaptive degree distribution, adaptive weight rotation allocation, and maximum weight constraints. Compared to previous schemes, the proposed solution in this paper further reduces the decoding overhead and recovery latency of less important modality, thus improving resource utilization.Feedback-Aided Rateless Codes Unequal Error Protection for Multimodal CommunicationJunpeng Yin, Yusun Fu, Haobo Huang, Shanghai Jiao Tong University