53 research outputs found

    Multi-Channel Random Access with Replications

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    This paper considers a class of multi-channel random access algorithms, where contending devices may send multiple copies (replicas) of their messages to the central base station. We first develop a hypothetical algorithm that delivers a lower estimate for the access delay performance within this class. Further, we propose a feasible access control algorithm achieving low access delay by sending multiple message replicas, which approaches the performance of the hypothetical algorithm. The resulting performance is readily approximated by a simple lower bound, which is derived for a large number of channels.Comment: 5 pages, 2 figures, accepted by ISIT 201

    System-Level Dynamics of Highly Directional Distributed Networks

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    While highly directional communications may offer considerable improvements in the link data rate and over-the-air latency of high-end wearable devices, the system-level capacity trade-offs call for separate studies with respect to the employed multiple access procedures and the network dynamics in general. This letter proposes a framework for estimating the system-level area throughput in dynamic distributed networks of highly-directional paired devices. We provide numerical expressions for the steady-state distribution of the number of actively communicating pairs and the probability of successful session initialization as well as derive the corresponding closed-form approximation for dense deployments.Comment: Accepted to IEEE Wireless Communications Letters on April 5, 2021. Copyright may be transferred without further notice after which this version may become non-availabl

    Resource-Efficient Federated Hyperdimensional Computing

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    In conventional federated hyperdimensional computing (HDC), training larger models usually results in higher predictive performance but also requires more computational, communication, and energy resources. If the system resources are limited, one may have to sacrifice the predictive performance by reducing the size of the HDC model. The proposed resource-efficient federated hyperdimensional computing (RE-FHDC) framework alleviates such constraints by training multiple smaller independent HDC sub-models and refining the concatenated HDC model using the proposed dropout-inspired procedure. Our numerical comparison demonstrates that the proposed framework achieves a comparable or higher predictive performance while consuming less computational and wireless resources than the baseline federated HDC implementation.Comment: Accepted to Federated Learning Systems (FLSys) workshop, in Conjunction with the 6th MLSys Conference (MLSys 2023

    A Concise Review of 5G New Radio Capabilities for Directional Access at mmWave Frequencies

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    In this work, we briefly outline the core 5G air interface improvements introduced by the latest New Radio (NR) specifications, as well as elaborate on the unique features of initial access in 5G NR with a particular emphasis on millimeter-wave (mmWave) frequency range. The highly directional nature of 5G mmWave cellular systems poses a variety of fundamental differences and research problem formulations, and a holistic understanding of the key system design principles behind the 5G NR is essential. Here, we condense the relevant information collected from a wide diversity of 5G NR standardization documents (based on 3GPP Release 15) to distill the essentials of directional access in 5G mmWave cellular, which becomes the foundation for any corresponding system-level analysis.Comment: 14 pages, 6 figures, 4 tables, published in proceedings of International Conference on Next Generation Wired/Wireless Networking, NEW2AN 2018, St. Petersburg, Russi

    Effects of Micro-Scale Mobility and Beam Misalignment in On-Body mmWave Systems

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    Wearable devices positioned on a human body have challenges in millimeter-wave (mmWave) communication due to micro-scale mobility, such as subtle shakes and rotations. These movements can compromise the radio link performance. It may be problematic for high-rate immersive applications, where this can lead to substantial degradation in the user’s quality of experience. In this letter, we propose a framework to quantify the impact of micro-scale mobility and beam misalignment on the performance of on-body mmWave links. Our findings reveal that for varying levels of beam misalignment, it is possible to adjust the antenna half-power beamwidth to enhance the data rates.Peer reviewe

    Path Loss Characterization for Intra-Vehicle Wearable Deployments at 60 GHz

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    In this work, we present the results of a wideband measurement campaign at 60 GHz conducted inside a Linkker electric city bus. Targeting prospective millimeter-wave (mmWave) public transportation wearable scenarios, we mimic a typical deployment of mobile high-end consumer devices in a dense environment. Specifically, our intra-vehicle deployment includes one receiver and multiple transmitters corresponding to a mmWave access point and passengers' wearable and hand-held devices. While the receiver is located in the front part of the bus, the transmitters repeat realistic locations of personal devices (i) at the seat level (e.g., a hand-held device) and (ii) at a height 70 cm above the seat (e.g., a wearable device: augmented reality glasses or a head-mounted display). Based on the measured received power, we construct a logarithmic model for the distance-dependent path loss. The parametrized models developed in the course of this study have the potential to become an attractive ground for the link budget estimation and interference footprint studies in crowded public transportation scenarios.Comment: 4 pages, 8 figures, 1 table, accepted to EuCAP 201

    Performance Scaling of mmWave Personal IoT Networks (PINs) for XR Applications

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    To provide a high-quality user experience in Extended Reality (XR) applications, high-throughput and low-latency communication is essential. A promising solution is the use of distributed networks operating in the higher frequency bands, such as millimeter-wave (mmWave) wearable Personal IoT Networks (PINs). However, in crowded environments, intra-network interactions can disrupt the Quality of Experience (QoE) for users. To improve the QoE, the understanding of the system-level performance trade-offs in these networks is important. This paper investigates the impact of various system parameters on the system-level performance of mmWave wearable PINs with 3D beamforming and data rate adaptation to the channel conditions in an environment with human body blockage. We employ an analytical methodology that combines stochastic geometry and queueing theory to devise an expression for the stationary distribution of the system and use it to compute the key metrics that describe the system-level performance. To assess mmWave PINs for XR in crowded environments, we examine the system operation trade-offs and explore the performance scaling.Peer reviewe
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