Block compressed sensing based distributed resource allocation for M2M communications
| Autor: | Chan Zhou, Peter Jung, Slawomir Stanczak, Yunyan Chang |
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| Rok vydání: | 2016 |
| Předmět: |
Computer science
Distributed computing 05 social sciences Real-time computing 050801 communication & media studies 020206 networking & telecommunications 02 engineering and technology Telecommunications network Base station 0508 media and communications Compressed sensing Robustness (computer science) 0202 electrical engineering electronic engineering information engineering Cluster (physics) Resource allocation |
| Zdroj: | ICASSP |
| DOI: | 10.1109/icassp.2016.7472386 |
| Popis: | In this paper, we utilize the framework of compressed sensing (CS) for device detection and distributed resource allocation in large-scale machine-to-machine (M2M) communication networks. The devices are partitioned into clusters according to some pre-defined criteria, e.g., proximity or service type. Moreover, by the sparse nature of the event occurrence in M2M communications, the activation pattern of the M2M devices can be formulated as a particular block sparse signal with additional in-block structure in CS based applications. This paper introduces a novel scheme for distributed resource allocation to the M2M devices based on block-CS related techniques, which mainly consists of three phases: (1) In a full-duplex acquisition phase, the network activation pattern is collected in a distributed manner. (2) The base station detects the active clusters and the number of active devices in each cluster, and then assigns a certain amount of resources accordingly. (3) Each active device detects the order of its index among all the active devices in the cluster and accesses the corresponding resource for transmission. The proposed scheme can efficiently reduce the acquisition time with much less computation complexity compared with standard CS algorithms. Finally, extensive simulations confirm the robustness of the proposed scheme under noisy conditions. |
| Databáze: | OpenAIRE |
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