6 research outputs found

    Joint Source-Channel Coding for Semantics-Aware Grant-Free Radio Access in IoT Fog Networks

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    A fog-radio access network (F-RAN) architecture is studied for an Internet-of-Things (IoT) system in which wireless sensors monitor a number of multi-valued events and transmit in the uplink using grant-free random access to multiple edge nodes (ENs). Each EN is connected to a central processor (CP) via a finite-capacity fronthaul link. In contrast to conventional information-agnostic protocols based on separate source-channel (SSC) coding, where each device uses a separate codebook, this paper considers an information-centric approach based on joint source-channel (JSC) coding via a non-orthogonal generalization of type-based multiple access (TBMA). By leveraging the semantics of the observed signals, all sensors measuring the same event share the same codebook (with non-orthogonal codewords), and all such sensors making the same local estimate of the event transmit the same codeword. The F-RAN architecture directly detects the events values without first performing individual decoding for each device. Cloud and edge detection schemes based on Bayesian message passing are designed and trade-offs between cloud and edge processing are assessed.Comment: submitted for publicatio

    Joint Source-Channel Coding and Bayesian Message Passing Detection for Grant-Free Radio Access in IoT

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    Consider an Internet-of-Things (IoT) system that monitors a number of multi-valued events through multiple sensors sharing the same bandwidth. Each sensor measures data correlated to one or more events, and communicates to the fusion center at a base station using grant-free random access whenever the corresponding event is active. The base station aims at detecting the active events, and, for each active event, to determine a scalar value describing each active event's state. A conventional solution based on Separate Source-Channel (SSC) coding would use a separate codebook for each sensor and decode the sensors' transmitted packets at the base station in order to subsequently carry out events' detection. In contrast, this paper considers a potentially more efficient solution based on Joint Source-Channel (JSC) coding via a non-orthogonal generalization of Type-Based Multiple Access (TBMA). Accordingly, all sensors measuring the same event share the same codebook (with non-orthogonal codewords), and the base station directly detects the events' values without first performing individual decoding for each sensor. A novel Bayesian message-passing detection scheme is developed for the proposed TBMA-based protocol, and its performance is compared to conventional solutions.Comment: submitted for conference publicatio

    Semantic Communication for Edge Intelligence: Theoretical Foundations and Implications on Protocols

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    Semantic communication has recently attracted considerable attention, mainly motivated by the trend of developing "task-oriented" communication solutions that tailor resource consumption to the task at hand. Despite the general intuition that semantic communication may contribute to more efficient system design, there have been only a few concrete attempts to implement aspects of it in practice. To help bridge this gap, in this paper, we revisit the theoretical foundations of semantic communication and address the possible implications on the protocol and system design. The focus is on two perspectives of semantic communication: (i) a goal-oriented perspective, which unifies aspects of traffic generation, communication, and control, with emphasis on the definition of appropriate semantic- aware metrics, and (ii) a semantic operability perspective, which extends the notion of data exchange through standardized interfaces (interoperability), to include the meaning or, more generally, the significance of data. We discuss applications of the concepts in scenarios such as robotic control and health monitoring

    Experimental Evaluation of NB-IoT Private Networks for Process Automation

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    Narrowband Internet-of-Things (NB-IoT) is a 3rd generation partnership project (3GPP) standardized cellular technology, adopted for 5G and optimized for massive Machine Type Communication (mMTC). Applications are anticipated around infrastructure monitoring, asset management, smart city and smart energy applications. In this paper, we evaluate the suitability of NB-IoT for private (campus) networks in industrial environments, including complex cloud-based applications around process automation. An end-to-end system has been developed, comprising of a sensor unit connected to a NB-IoT modem, a base station (gNodeB) equipped with a beamforming array and a local (private) network architecture comprising a sensor management system in the edge cloud. The experimental study includes field tests in realistic industrial environments with latency, reliability and coverage measurements. The results show a good suitability of NB-IoT for process automation with high scalability, low-power requirements and moderate latency requirements
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