Uplink Resource Allocation for Multi-Cluster Internet-of-Things Deployment Underlaying Cellular Networks

ElHalawany, Basem M.; Hashad, Omnia; Wu, Kaishun; Eldien, Adly S. Tag

doi:10.1007/s11036-019-01288-6

Cited by 17 publications

(9 citation statements)

References 33 publications

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“…Well scheduling for radio frames avoid the accumulative delay due to multiple trial of RA requests until success to acquire data channel even with using alternative techniques as D2D [41].…”

Section: Simulation Results Analysis and Discussionmentioning

confidence: 99%

NB‐IoT optimisation: Holistic view for smart cities applications with smart meters networks case study

et al. 2020

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The future demands for smart-cities applications impose maximising the resources utilisation. This study achieves two main objectives to comply with fifth-generation networks goals. First one is to enhance the Narrowband-Internet of Things (NB-IoT) spectralefficiency. The second is to alleviate the burden of two issues: The signalling during each transmission request for smart-meters (SM) and queuing burden. First, we model the uplink scheduler for the NB-IoT access network using state-machine modelling methodology on Simulink environment. The simulation result is verified and validated with trusted modelling technique. Second, we optimise the NB-IoT uplink scheduler which exploits the periodicity nature of SMs applications with putting envisage considering the emergency conditions. This is done by proposing integrated scheduling protocol which classifies the IoT traffic types and rearranges the transmission times of different SMs utilities and draws a map for the transmission schedule of them to better utilise the sparse time resources. The proposal comprises architecture, signalling, and algorithms. The optimisation is evaluated in term of numbers of SMs versus four spectral performance indicators; utilisation, efficiency, setup-success-percentage, and session-drop-rate according to a case study. The simulation results prove the ability of our proposal to increase the spectrum-utilisation to 17.47%. This enhancement reflects on spectral-efficiency that improved doubled.

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Section: Simulation Results Analysis and Discussionmentioning

confidence: 99%

NB‐IoT optimisation: Holistic view for smart cities applications with smart meters networks case study

et al. 2020

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“…, and θ is the residual interference power ratio due to imperfect SIC, which is assumed to be the same for all users without loss of generality. Given the SINRs in (2), the achievable data rates of the three nodes at the two time slots are given as follows…”

Section: Network Modelmentioning

confidence: 99%

“…Different promising applications and services have been proposed underlaying 5G such as realtime high-definition video broadcasting, massive deployment of machine-to-machine (M2M) communications and Internetof-Things (IoT) services [1]. With this huge demand of resources, spectral efficiency becomes a critical aspect for managing the access to the core network [2]. Several multiple access techniques have been investigated for exploiting the spectrum to face the congestion problem.…”

Section: Introductionmentioning

confidence: 99%

Uplink IoT Networks: Time-Division Priority-Based Non-Orthogonal Multiple Access Approach

ElHalawany¹,

El-Banna²,

Wu³

et al. 2021

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Non-orthogonal multiple access (NOMA) has been investigated to support massive connectivity for Internet-of-things (IoT) networks. However, since most IoT devices suffer from limited power and decoding capabilities, it is not desirable to pair a large number of devices simultaneously, which encourages two-user NOMA grouping. Additionally, most existing techniques have not considered the diversity in the target QoS of IoT devices, which may lead to spectrum inefficiency. Few investigations have partially considered that issue by using an order-based power allocation (OPA) approach, where the power is allocated according to the order to the user's target throughput within a priority-based NOMA (PNOMA) group. However, this does not fully capture the effects of diversity in the values of the users' target throughputs. In this work, we handle both problems by considering a throughput-based power allocation (TPA) approach, that captures the QoS diversity, within a three-users PNOMA group as a compromise between spectral efficiency and complexity. Specifically, we investigate the performance of a time-division PNOMA (TD-PNOMA) scheme, where the transmission time is divided into two-time slots with two-users per PNOMA group. The performance of such TD-PNOMA is compared with a fully PNOMA (F-PNOMA) scheme, where the three users share the whole transmission time, in terms of the ergodic capacity under imperfect successive interference cancellation (SIC). The results reveal the superiority of TPA compared with OPA approach in both schemes, besides that the throughput of both schemes can outperform each other under imperfect SIC based on the transmit signal-to-noise ratio and the deployment scenarios.

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“…As a means for direct communication between devices in proximity underlaying cellular networks, D2D has emerged as a key technology with promises to improve utilization, energy efficiency (EE), and spectrum efficiency. Moreover, D2D communication could support some interesting features such as low power, short-range, long battery life, and massive connectivity for enabling Internet-of-Things (IoT) deployment underlaying cellular network [1], [2]. Additionally, D2D communication provides several benefits for the core network including load balancing, traffic offloading, better coverage for edge users, and satisfying the quality of service (QoS) requirements [3], [4].…”

Section: Introductionmentioning

confidence: 99%

“…Those differences include (1) The interference from the eNB in the downlink is much higher than the interference from UE in the uplink, which limits the channel sharing availability. (2) The control is centralized at the eNB, which has higher processing capabilities than the UE, thus, allows better interference management. (3) The traffic load in the uplink is less than in the downlink, which gives higher spectrum efficiency when sharing the uplink resources rather than the downlink.…”

Section: Introductionmentioning

confidence: 99%

Resources Allocation in Underlay Device-to-Device Communications Networks: A Reduced-Constraints Approach

et al. 2020

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Device-to-Device (D2D) communications underlaying cellular networks have emerged as a necessity for a substantial increase in the system throughput and the number of active devices for the future cellular networks. In underlay D2D networks, it is conventional to use different interference management (IM) techniques to allow D2D transmitters to reuse the cellular users' subcarriers. Conventionally, those IM techniques pair a specific number (one or more) of D2D transmitters to each subcarrier and/or allow each D2D transmitter to transmit on a specific number of subcarriers simultaneously in order to achieve the target rates. Due to the mixed-integer nature of those IM techniques, convex optimization techniques can not be used, and usually complex heuristic or game-theoretic approaches are exploited. In this paper, we introduce a reduced-constraints approach to seek sub-optimal joint power allocation and channel assignment solutions for two non-convex, mixed-integer, and non-linear programs (MINLP). Specifically, via the reduced-constraints approach and variable transformation techniques, we can exploit primal-dual algorithms to solve system power minimization and energy-efficiency maximization problems. Extensive numerical simulation results show that the proposed approach outperforms state-of-the-art techniques.

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Uplink Resource Allocation for Multi-Cluster Internet-of-Things Deployment Underlaying Cellular Networks

Cited by 17 publications

References 33 publications

NB‐IoT optimisation: Holistic view for smart cities applications with smart meters networks case study

NB‐IoT optimisation: Holistic view for smart cities applications with smart meters networks case study

Uplink IoT Networks: Time-Division Priority-Based Non-Orthogonal Multiple Access Approach

Resources Allocation in Underlay Device-to-Device Communications Networks: A Reduced-Constraints Approach

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