1,230 research outputs found

    Sparse Message Passing Based Preamble Estimation for Crowded M2M Communications

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    Due to the massive number of devices in the M2M communication era, new challenges have been brought to the existing random-access (RA) mechanism, such as severe preamble collisions and resource block (RB) wastes. To address these problems, a novel sparse message passing (SMP) algorithm is proposed, based on a factor graph on which Bernoulli messages are updated. The SMP enables an accurate estimation on the activity of the devices and the identity of the preamble chosen by each active device. Aided by the estimation, the RB efficiency for the uplink data transmission can be improved, especially among the collided devices. In addition, an analytical tool is derived to analyze the iterative evolution and convergence of the SMP algorithm. Finally, numerical simulations are provided to verify the validity of our analytical results and the significant improvement of the proposed SMP on estimation error rate even when preamble collision occurs.Comment: submitted to ICC 2018 with 6 pages and 4 figure

    Next Generation M2M Cellular Networks: Challenges and Practical Considerations

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    In this article, we present the major challenges of future machine-to-machine (M2M) cellular networks such as spectrum scarcity problem, support for low-power, low-cost, and numerous number of devices. As being an integral part of the future Internet-of-Things (IoT), the true vision of M2M communications cannot be reached with conventional solutions that are typically cost inefficient. Cognitive radio concept has emerged to significantly tackle the spectrum under-utilization or scarcity problem. Heterogeneous network model is another alternative to relax the number of covered users. To this extent, we present a complete fundamental understanding and engineering knowledge of cognitive radios, heterogeneous network model, and power and cost challenges in the context of future M2M cellular networks

    Reliable machine-to-machine multicast services with multi-radio cooperative retransmissions

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s11036-015-0575-6The 3GPP is working towards the definition of service requirements and technical solutions to provide support for energy-efficient Machine Type Communications (MTC) in the forthcoming generations of cellular networks. One of the envisioned solutions consists in applying group management policies to clusters of devices in order to reduce control signaling and improve upon energy efficiency, e.g., multicast Over-The-Air (OTA) firmware updates. In this paper, a Multi-Radio Cooperative Retransmission Scheme is proposed to efficiently carry out multicast transmissions in MTC networks, reducing both control signaling and improving energy-efficiency. The proposal can be executed in networks composed by devices equipped with multiple radio interfaces which enable them to connect to both a cellular access network, e.g., LTE, and a short-range MTC area network, e.g., Low-Power Wi-Fi or ZigBee, as foreseen by the MTC architecture defined by ETSI. The main idea is to carry out retransmissions over the M2M area network upon error in the main cellular link. This yields a reduction in both the traffic load over the cellular link and the energy consumption of the devices. Computer-based simulations with ns-3 have been conducted to analyze the performance of the proposed scheme in terms of energy consumption and assess its superior performance compared to non-cooperative retransmission schemes, thus validating its suitability for energy-constrained MTC applications.Peer ReviewedPostprint (author's final draft

    On the Fundamental Limits of Random Non-orthogonal Multiple Access in Cellular Massive IoT

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    Machine-to-machine (M2M) constitutes the communication paradigm at the basis of Internet of Things (IoT) vision. M2M solutions allow billions of multi-role devices to communicate with each other or with the underlying data transport infrastructure without, or with minimal, human intervention. Current solutions for wireless transmissions originally designed for human-based applications thus require a substantial shift to cope with the capacity issues in managing a huge amount of M2M devices. In this paper, we consider the multiple access techniques as promising solutions to support a large number of devices in cellular systems with limited radio resources. We focus on non-orthogonal multiple access (NOMA) where, with the aim to increase the channel efficiency, the devices share the same radio resources for their data transmission. This has been shown to provide optimal throughput from an information theoretic point of view.We consider a realistic system model and characterise the system performance in terms of throughput and energy efficiency in a NOMA scenario with a random packet arrival model, where we also derive the stability condition for the system to guarantee the performance.Comment: To appear in IEEE JSAC Special Issue on Non-Orthogonal Multiple Access for 5G System

    Data Aggregation and Packet Bundling of Uplink Small Packets for Monitoring Applications in LTE

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    In cellular massive Machine-Type Communications (MTC), a device can transmit directly to the base station (BS) or through an aggregator (intermediate node). While direct device-BS communication has recently been in the focus of 5G/3GPP research and standardization efforts, the use of aggregators remains a less explored topic. In this paper we analyze the deployment scenarios in which aggregators can perform cellular access on behalf of multiple MTC devices. We study the effect of packet bundling at the aggregator, which alleviates overhead and resource waste when sending small packets. The aggregators give rise to a tradeoff between access congestion and resource starvation and we show that packet bundling can minimize resource starvation, especially for smaller numbers of aggregators. Under the limitations of the considered model, we investigate the optimal settings of the network parameters, in terms of number of aggregators and packet-bundle size. Our results show that, in general, data aggregation can benefit the uplink massive MTC in LTE, by reducing the signalling overhead.Comment: to appear in IEEE Networ
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