Joint access control and resource allocation for machine type communications

Guo, Jian; Zhang, Xuefei; Wang, Ruiqi; Tao, Xiaofeng

doi:10.1109/iccchinaw.2017.8355283

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…In this section, our main goal is to compare the performance of MC-JFS against those of MC-RAB and MC-ERAB, which serve as reactive benchmark protocols. To this end, first, 30 Note that there is no separate access channel in MC-RAB. Thus, data reception at G has already begun in the first slot, which contains both the value of p Jm and those bits of Jm that fall in the first slot.…”

Section: Resultsmentioning

confidence: 99%

“…In [29] and [30], joint access control and resource allocation schemes were proposed for massive access of M2M devices. While both the access and data scheduling aspects have been handled in these works, the models and the simulation results therein are based on random access and do not utilize any forecasting of M2M traffic.…”

Section: Relationship To the State Of The Artmentioning

confidence: 99%

“…The device i prepends the value of p Jm to the set of bits Jm that are transmitted on channel m ∈ M sel j [t]. 29 For each channel m ∈ Jm without waiting for successive such sets to accumulate in order to ensure that the deadline of this set of bits does not expire due to an unnecessary delay at G. M sel j [t], whenever G receives the value of p Jm , if p Jm ≥ 2, G reserves the next (p Jm − 1) slots 30 of channel m for the set of bits Jm and acknowledges the reception of Jm by sending the set of slot-channel pairs that have been reserved for Jm to all of the devices 31 (including i). We shall denote this acknowledgment by ACK Jm .…”

Section: Reactive Protocol Benchmarks: Mc-rab and Mc-erabmentioning

confidence: 99%

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Multi-Channel Joint Forecasting-Scheduling for the Internet of Things

et al. 2020

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We develop a methodology for Multi-Channel Joint Forecasting-Scheduling (MC-JFS) targeted at solving the Medium Access Control (MAC) layer Massive Access Problem of Machine-to-Machine (M2M) communication in the presence of multiple channels, as found in Orthogonal Frequency Division Multiple Access (OFDMA) systems. In contrast with the existing schemes that merely react to current traffic demand, Joint Forecasting-Scheduling (JFS) forecasts the traffic generation pattern of each Internet of Things (IoT) device in the coverage area of an IoT Gateway and schedules the uplink transmissions of the IoT devices over multiple channels in advance, thus obviating contention, collision and handshaking, which are found in reactive protocols. In this paper, we present the general form of a deterministic scheduling optimization program for MC-JFS that maximizes the total number of bits that are delivered over multiple channels by the delay deadlines of the IoT applications. In order to enable real-time operation of the MC-JFS system, first, we design a heuristic, called Multi-Channel Look Ahead Priority based on Average Load (MC-LAPAL), that solves the general form of the scheduling problem. Second, for the special case of identical channels, we develop a reduction technique by virtue of which an optimal solution of the scheduling problem is computed in real time. We compare the network performance of our MC-JFS scheme against Multi-Channel Reservation-based Access Barring (MC-RAB) and Multi-Channel Enhanced Reservation-based Access Barring (MC-ERAB), both of which serve as benchmark reactive protocols. Our results show that MC-JFS outperforms both MC-RAB and MC-ERAB with respect to uplink cross-layer throughput and transmit energy consumption, and that MC-LAPAL provides high performance as an MC-JFS heuristic. Furthermore, we show that the computation time of MC-LAPAL scales approximately linearly with the number of IoT devices. This work serves as a foundation for building scalable JFS schemes at IoT Gateways in the near future.

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Section: Resultsmentioning

confidence: 99%

Section: Relationship To the State Of The Artmentioning

confidence: 99%