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Found 9 papers, 0 papers with code
Distributed Intelligent Integrated Sensing and Communications: The 6G-DISAC Approach
This paper introduces the concept of Distributed Intelligent integrated Sensing and Communications (DISAC), which expands the capabilities of Integrated Sensing and Communications (ISAC) towards distributed architectures.
Towards Distributed and Intelligent Integrated Sensing and Communications for 6G Networks
This paper introduces the distributed and intelligent integrated sensing and communications (DISAC) concept, a transformative approach for 6G wireless networks that extends the emerging concept of integrated sensing and communications (ISAC).
V2X Sidelink Positioning in FR1: Scenarios, Algorithms, and Performance Evaluation
In this paper, we investigate sub-6 GHz V2X sidelink positioning scenarios in 5G vehicular networks through a comprehensive end-to-end methodology encompassing ray-tracing-based channel modeling, novel theoretical performance bounds, high-resolution channel parameter estimation, and geometric positioning using a round-trip-time (RTT) protocol.
Analysis of V2X Sidelink Positioning in sub-6 GHz
Radio positioning is an important part of joint communication and sensing in beyond 5G communication systems.
Reconstruction-Computation-Quantization (RCQ): A Paradigm for Low Bit Width LDPC Decoding
RCQ facilitates dynamic non-uniform quantization to achieve good frame error rate (FER) performance with very low message precision.
A Reconstruction-Computation-Quantization (RCQ) Approach to Node Operations in LDPC Decoding
In contrast, the proposed RCQ decoder may be applied to any off-the-shelf LDPC code, including those with a large fraction of degree-2 variable nodes. Our simulations show that a 4-bit Min-Sum RCQ decoder delivers frame error rate (FER) performance around 0. 1dB of full-precision belief propagation (BP) for the IEEE 802. 11 standard LDPC code in the low SNR region. The RCQ decoder actually outperforms full-precision BP in the high SNR region because it overcomes elementary trapping sets that create an error floor under BP decoding.
Trainable Communication Systems: Concepts and Prototype
We consider a trainable point-to-point communication system, where both transmitter and receiver are implemented as neural networks (NNs), and demonstrate that training on the bit-wise mutual information (BMI) allows seamless integration with practical bit-metric decoding (BMD) receivers, as well as joint optimization of constellation shaping and labeling.
Information Theory Signal Processing Information Theory
Joint Learning of Geometric and Probabilistic Constellation Shaping
In this work, we show how autoencoders can be leveraged to perform probabilistic shaping of constellations.
Decoding of Non-Binary LDPC Codes Using the Information Bottleneck Method
Recently, a novel lookup table based decoding method for binary low-density parity-check codes has attracted considerable attention.
