Emergent communication for AR

Mobile augmented reality (MAR) is widely acknowledged as one of the ubiquitous interfaces to the digital twin and Metaverse, demanding unparalleled levels of latency, computational power, and energy efficiency. The existing solutions for realizing MAR combine multiple technologies like edge, cloud computing, and fifth-generation (5G) networks. However, the inherent communication latency of visual data imposes apparent limitations on the quality of experience (QoE). To address the challenge, we propose an emergent semantic communication framework to learn the communication protocols in MAR. Specifically, we train two agents through a modified Lewis signaling game to emerge a discrete communication protocol spontaneously. Based on this protocol, two agents can communicate about the abstract idea of visual data through messages with extremely small data sizes in a noisy channel, which leads to message errors. To better simulate real-world scenarios, we incorporate channel uncertainty into our training process. Experiments have shown that the proposed scheme has better generalization on unseen objects than traditional object recognition used in MAR and can effectively enhance communication efficiency through the utilization of small-size messages

Near-Field Integrated Sensing and Communication: Performance Analysis and Beamforming Design

This paper explores the potential of near-field beamforming (NFBF) in integrated sensing and communication (ISAC) systems with extremely large-scale arrays (XL-arrays). The large-scale antenna arrays increase the possibility of having communication users and targets of interest in the near field of the base station (BS). The paper first establishes the models of electromagnetic (EM) near-field spherical waves and far-field plane waves. With the models, we analyze the near-field beam focusing ability and the far-field beam steering ability by finding the gain-loss mathematical expression caused by the far-field steering vector mismatch in the near-field case. We formulate the NFBF design problem as minimizing the weighted summation of radar and the communication beamforming errors under a total power constraint and solve this quadratically constrained quadratic programming (QCQP) problem using the least squares (LS) method. Moreover, the Cram\'er-Rao bound (CRB) for target parameter estimation is derived to verify the performance of NFBF. Furthermore, we also perform power minimization using convex optimization while ensuring the required communication and sensing quality-of-service (QoS). The simulation results show the influence of model mismatch on near-field ISAC and the performance gain of transmit beamforming from the additional distance dimension of near-field.Comment: under revie

Green Holographic MIMO Communications With A Few Transmit Radio Frequency Chains

Holographic multiple-input multiple-output (MIMO) communications are widely recognized as a promising candidate for the next-generation air interface. With holographic MIMO surface, the number of the spatial degrees-of-freedom (DoFs) considerably increases and also significantly varies as the user moves. To fully employ the large and varying number of spatial DoFs, the number of equipped RF chains has to be larger than or equal to the largest number of spatial DoFs. However, this causes much waste as radio frequency (RF) chains (especially the transmit RF chains) are costly and power-hungry. To avoid the heavy burden, this paper investigates green holographic MIMO communications with a few transmit RF chains under an electromagnetic-based communication model. We not only look at the fundamental capacity limits but also propose an effective transmission, namely non-uniform holographic pattern modulation (NUHPM), to achieve the capacity limit in the high signal-to-noise (SNR) regime. The analytical result sheds light on the green evaluation of MIMO communications, which can be realized by increasing the size of the antenna aperture without increasing the number of transmit RF chains. Numerical results are provided to verify our analysis and to show the great performance gain by employing the additional spatial DoFs as modulation resources.Comment: 10 figures; has been accepted by TGC

Analysis of Reliability Correlation Degree of Rolling Bearings Based on Zero-Failure Data

Modern equipment has higher requirements for the reliability of rolling bearings. The time and economic cost of obtaining bearing failure data through test methods are getting higher. Usually, truncation time tests of small sample are used to obtain zero-failure data of bearings. Based on the zero-failure data model and multi-layer Bayesian theory, this paper improves the reliability evaluation method of rolling bearings by changing the values of hyperparameters, and calculates the estimated value of failure probability at each truncation time to obtain the reliability of the bearing. This paper adopts the theory of grey relational degree to analyze the relationship and change law of bearing reliability at each truncation time, to understand the reliability change trend of rolling bearing more comprehensively. Experiments show that the method is reasonable

Semantic Communications with Ordered Importance using ChatGPT

This letter proposes a novel semantic communication scheme with ordered importance (SCOI) using the chat generative pre-trained transformer (ChatGPT). In the proposed SCOI scheme, ChatGPT plays the role of a consulting assistant. Given a message to be transmitted, the transmitter first queries ChatGPT to output the importance order of each word. According to the importance order, the transmitter then performs an unequal error protection transmission strategy to make the transmission of essential words more reliable. Unlike the existing semantic communication schemes, SCOI is compatible with existing source-channel separation designs and can be directly embedded into current communication systems. Our experimental results show that both the transmission bit error rate (BER) of important words and the semantic loss measured by ChatGPT are much lower than the existing communication schemes