Efficient transmission strategy selection algorithm for M2M communications: An evolutionary game approach

Hamdoun, Safa; Rachedi, Abderrezak; Tembiné, Hamidou; Ghamri‐Doudane, Yacine

doi:10.1109/nca.2016.7778632

Cited by 15 publications

(16 citation statements)

References 12 publications

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“…approach is proposed in [14] for optimizing the transmission strategy in a device-to-device (D2D) enabled LTE network in which each MTD chooses to act noncooperatively or cooperatively with other MTDs using the same resources. In [15], the problem of uplink user association of IoT devices is studied in a dense small cell network using a mean-field game.…”

Section: A Related Workmentioning

confidence: 99%

“…However, these works [8]- [14], [16], [17] typically rely on the concept of a Nash equilibrium to solve the studied resource allocation problems. Such a conventional Nash equilibrium solution may not be suitable to solve the distributed resource allocation when the optimization is done at the IoT devices' end.…”

Section: A Related Workmentioning

confidence: 99%

“…The work in [13] considers a heterogeneous system of MTDs in which nodes can use different routing and network coding schemes to optimize heterogeneous QoS requirements. An evolutionary gameapproach is proposed in [14] for optimizing the transmission strategy in a device-to-device (D2D) enabled LTE network in which each MTD chooses to act noncooperatively or cooperatively with other MTDs using the same resources. In [15], the problem of uplink user association of IoT devices is studied in a dense small cell network using a mean-field game.However, these works [8]- [14], [16], [17] typically rely on the concept of a Nash equilibrium to solve the studied resource allocation problems.…”

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confidence: 99%

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Cognitive Hierarchy Theory for Distributed Resource Allocation in the Internet of Things

Abuzainab

Saad

Hong

et al. 2017

IEEE Trans. Wireless Commun.

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In this paper, the problem of distributed resource allocation is studied for an Internet of Things (IoT) system, composed of a heterogeneous group of nodes compromising both machine-type devices (MTDs) and human-type devices (HTDs). The problem is formulated as a noncooperative game between the heterogeneous IoT devices that seek to find the optimal time allocation so as to meet their qualityof-service (QoS) requirements in terms of energy, rate and latency. Since the strategy space of each device is dependent on the actions of the other devices, the generalized Nash equilibrium (GNE) solution is first characterized, and the conditions for uniqueness of the GNE are derived. Then, to explicitly capture the heterogeneity of the devices, in terms of resource constraints and QoS needs, a novel and more realistic game-theoretic approach, based on the behavioral framework of cognitive hierarchy (CH) theory, is proposed. This approach is then shown to enable the IoT devices to reach a CH equilibrium (CHE) concept that takes into account the various levels of rationality corresponding to the heterogeneous computational capabilities and the information accessible for each one of the MTDs and HTDs. Simulation results show that the CHE solution maintains stable performance. In particular, the proposed CHE solution keeps the percentage of devices with satisfied QoS constraints above 96%for IoT networks containing up to 10,000 devices without considerably degrading the overall system performance in terms of the total utility. Simulation results also show that the proposed CHE solution brings a two-fold increase in the total rate of HTDs and deceases the total energy consumed by MTDs by 78% compared to the equal time policy. N. Abuzainab and W. Saad are with the department For example, the performance of MTDs that require ultra low latency or HTDs that require high data rates can can be severely affected by collisions. Thus, there is a need to design a new, distributed IoT multiple access scheme that can satisfy the requirements of devices with strict QoS constraints. A. Related WorksThere has been significant recent interest in developing resource allocation mechanisms suitable for the IoT such as in [8]-[14], [16], [17]. Centralized scheduling schemes for IoT LTE networks are proposed in [8]-[11]. In [8], a resource management scheme that dynamically allocates time resources between MTDs and HTDs based on current traffic conditions and QoS requirements. The works in [9] and [10] propose schemes that allocate the LTE resources to MTDs and HTDs based on a bipartite graph. In [11], the authors propose two seperate uplink scheduling schemes for HTDs and MTDs in an LTE system based on channel conditions and delay requirements while taking fairness into account. Other works such as in [12] and [13]adopted game-theoretic approaches for distributed resource allocation problems in the IoT. The authors in [12] study the problem of throughput maximization of MTDs under random access. However, in [12], devices are considered of equal ca...

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Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

mentioning

confidence: 99%

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Cognitive Hierarchy Theory for Distributed Resource Allocation in the Internet of Things

Abuzainab

Saad

Hong

et al. 2017

IEEE Trans. Wireless Commun.

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“…At the receiver side, user with better channel conditions will try to decode its own signal by employing successive interference cancellation (SIC) techniques. Cooperative relaying can improve the coverage, capacity, and reliability of wireless networks . In cooperative NOMA, users with better channel conditions can themselves act as relays for assisting the transmission of other users, or dedicated relays can even be deployed to improve the performance .…”

Section: Introductionmentioning

confidence: 99%

“…Cooperative relaying can improve the coverage, capacity, and reliability of wireless networks. [3][4][5] In cooperative NOMA, users with better channel conditions can themselves act as relays for assisting the transmission of other users, 6 or dedicated relays can even be deployed to improve the performance. 7 Recently, NOMA has been adopted by various standardizations, for example, multiuser superposition transmission (MUST) in third-generation partnership project long-term evolution (3GPP-LTE) and layered division multiplexing (LDM) in digital TV standard ATSC 3.…”

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confidence: 99%

Performance analysis of nonorthogonal multiple access‐based underlay cognitive relay network

Aswathi

Babu

2019

Int J Communication

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Summary This paper considers cooperative non‐orthogonal multiple access (NOMA) scheme in an underlay cognitive radio (CR) network. A single‐cell downlink cooperative NOMA system has been considered for the secondary network, consisting of a base station (BS) and two secondary users, ie, a far user and a near user. The BS employs NOMA signaling to send messages for the two secondary users where the near user is enabled to act as a half‐duplex decode‐and‐forward (DF) relay for the far user. We derive exact expressions for the outage probability experienced by both the users and the outage probability of the secondary system assuming the links to experience independent, nonidentically distributed Rayleigh fading. Further, we analyze the ergodic rates of both the users and the ergodic sum rate of the secondary network. The maximum transmit power constraint of the secondary nodes and the tolerable interference power constraint at the primary receiver are considered for the analysis. Further, the interference caused by the primary transmitter (PT) on the secondary network is also considered for the analysis. The performance of the proposed CR NOMA network has been observed to be significantly better than a CR network that uses conventional orthogonal multiple access (OMA) scheme. The analytical results are validated by extensive simulation studies.

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Antenna array techniques for nonuniform cell zooming and adaptive frequency planning

Lahiry

2018

Int J Communication

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This paper proposes the antenna array system and the techniques for the nonuniform cell zooming and adaptive frequency planning which is suitable for the energy-efficient LTE network and multitier 5G heterogeneous network. The antenna array system is designed for the beam width control and scan control in the azimuth plane. The beam tilt is controlled in the elevation plane to control the cell radius. The first feature of the antenna array system is to perform nonuniform sector size control in order to deal with the nonuniform traffic distribution. The second feature of the antenna array system is to control the beam scan in the azimuth plane for the adaptive frequency planning. The footprint control of the current work is evaluated considering the antenna array's radiation pattern and all the physical parameters. Adaptive frequency planning can mitigate cochannel interference (CCI), which may be caused due to the cell zooming techniques proposed in this work. The footprint simulations confirm that the antenna array system can control the sector size with the highest possible flexibility. The antenna array system due to these features can effectively mitigate the interference. The results also confirm that the current antenna array system outperforms the existing antenna array systems.

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Efficient transmission strategy selection algorithm for M2M communications: An evolutionary game approach

Cited by 15 publications

References 12 publications

Cognitive Hierarchy Theory for Distributed Resource Allocation in the Internet of Things

Cognitive Hierarchy Theory for Distributed Resource Allocation in the Internet of Things

Performance analysis of nonorthogonal multiple access‐based underlay cognitive relay network

Antenna array techniques for nonuniform cell zooming and adaptive frequency planning

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