Collision Avoidance Resource Allocation for LoRaWAN

The number of connected IoT devices is significantly increasing and it is expected to reach more than two dozens of billions of IoT connections in the coming years. Low Power Wide Area Networks (LPWAN) have become very relevant for this new paradigm due to features such as large coverage and low power consumption. One of the most appealing technologies among these networks is LoRaWAN. Although it may be considered as one of the most mature LPWAN platforms, there are still open gaps such as its capacity limitations. For this reason, this work proposes a collision avoidance resource allocation algorithm named the Collision Avoidance Resource Allocation (CARA) algorithm with the objective of significantly increase system capacity. CARA leverages the multichannel structure and the orthogonality of spreading factors in LoRaWAN networks to avoid collisions among devices. Simulation results show that, assuming ideal radio link conditions, our proposal outperforms in 95.2% the capacity of a standard LoRaWAN network and increases the capacity by almost 40% assuming a realistic propagation model. In addition, it has been verified that CARA devices can coexist with LoRaWAN traditional devices, thus allowing the simultaneous transmissions of both types of devices. Moreover, a proof-of-concept has been implemented using commercial equipment in order to check the feasibility and the correct operation of our solution.

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D2D Assisted Cellular Networks in Licensed and Unlicensed Spectrum: Matching-Iteration-Based Joint User Access and Resource Allocation

Algorithms ◽

10.3390/a14030080 ◽

2021 ◽

Vol 14 (3) ◽

pp. 80

Author(s):

Qiuqi Han ◽

Guangyuan Zheng ◽

Chen Xu

Keyword(s):

Resource Allocation ◽

Cellular Networks ◽

System Capacity ◽

System Throughput ◽

Unlicensed Spectrum ◽

Resource Allocation Algorithm ◽

User Access ◽

Limited Spectrum

Device-to-Device (D2D) communications, which enable direct communication between nearby user devices over the licensed spectrum, have been considered a key technique to improve spectral efficiency and system throughput in cellular networks (CNs). However, the limited spectrum resources cannot be sufficient to support more cellular users (CUs) and D2D users to meet the growth of the traffic data in future wireless networks. Therefore, Long-Term Evolution-Unlicensed (LTE-U) and D2D-Unlicensed (D2D-U) technologies have been proposed to further enhance system capacity by extending the CUs and D2D users on the unlicensed spectrum for communications. In this paper, we consider an LTE network where the CUs and D2D users are allowed to share the unlicensed spectrum with Wi-Fi users. To maximize the sum rate of all users while guaranteeing each user’s quality of service (QoS), we jointly consider user access and resource allocation. To tackle the formulated problem, we propose a matching-iteration-based joint user access and resource allocation algorithm. Simulation results show that the proposed algorithm can significantly improve system throughput compared to the other benchmark algorithms.

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An Efficient Resource Allocation Algorithm for Device-To-Device Communications

Applied Sciences ◽

10.3390/app9183816 ◽

2019 ◽

Vol 9 (18) ◽

pp. 3816 ◽

Cited By ~ 2

Author(s):

Saraereh ◽

Mohammed ◽

Khan ◽

Rabie ◽

Affess

Keyword(s):

Resource Allocation ◽

Optimal Algorithm ◽

Search Algorithm ◽

Low Complexity ◽

System Capacity ◽

Total System ◽

Resource Allocation Algorithm ◽

Allocation Algorithm ◽

Device To Device ◽

Total Capacity

In order to solve the problem of interference and spectrum optimization caused by D2D (device-to-device) communication multiplexing uplink channel of heterogeneous cellular networks, the allocation algorithm based on the many-to-one Gale-Shapley (M21GS) algorithm proposed in this paper can effectively solve the resource allocation problem of D2D users multiplexed cellular user channels in heterogeneous cellular network environments. In order to improve the utilization of the wireless spectrum, the algorithm allows multiple D2D users to share the channel resources of one cellular user and maintains the communication service quality of the cellular users and D2D users by setting the signal to interference and noise ratio (SINR) threshold. A D2D user and channel preference list are established based on the implemented system’s capacity to maximize the system total capacity objective function. Finally, we use the Kuhn–Munkres (KM) algorithm to achieve the optimal matching between D2D clusters and cellular channel to maximize the total capacity of D2D users. The MATLAB simulation is used to compare and analyze the total system capacity of the proposed algorithm, the resource allocation algorithm based on the delay acceptance algorithm, the random resource allocation algorithm and the optimal exhaustive search algorithm, and the maximum allowable access for D2D users. The simulation results show that the proposed algorithm has fast convergence and low complexity, and the total capacity is close to the optimal algorithm.

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Competitive Game Theoretic Clustering-Based Multiple UAV-Assisted NB-IoT Systems

Electronics ◽

10.3390/electronics10030356 ◽

2021 ◽

Vol 10 (3) ◽

pp. 356

Author(s):

Chunghyun Lee ◽

Gunhee Jang ◽

Nhu-Ngoc Dao ◽

Demeke Shumeye Lakew ◽

Cheol Lee ◽

...

Keyword(s):

Resource Allocation ◽

Clustering Algorithm ◽

Critical Role ◽

System Capacity ◽

Coverage Area ◽

Competitive Game ◽

Np Hard Problem ◽

Aerial Vehicle ◽

Game Theoretic ◽

Iot Devices

Unmanned aerial vehicle (UAV) communication is regarded as a promising technology for lightweight Internet of Things (IoT) communications in narrowband-IoT (NB-IoT) systems deployed in rugged terrain. In such UAV-assisted NB-IoT systems, the optimal UAV placement and resource allocation play a critical role. Consequently, the joint optimization of the UAV placement and resource allocation is considered in this study to improve the system capacity. Because the considered optimization problem is an NP-hard problem and owing to its non-convex property, it is difficult to optimize both the UAV placement and resource allocation simultaneously. Therefore, a competitive clustering algorithm has been developed by exchanging strategies between the UAV and the adjacent IoT devices to optimize the UAV placement. With multiple iterations, the UAV and the IoT devices within the coverage area of the UAV, converge their clustering strategies, which are suboptimal, to satisfy both sides. The bordering IoT devices of the adjacent clusters are then migrated heuristically toward each other to obtain the optimal system capacity maximization. Finally, the transmission throughput is optimized using the Nash equilibrium. The simulation results demonstrate that the algorithms proposed in this study exhibit rapid convergence, within 10 iterations, even in a large environment. The performance evaluation demonstrates that the proposed scheme improves the system capacity of the existing schemes by approximately 28%.

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An Efficient Resource Allocation Algorithm for OFDM-Based NOMA in 5G Systems

Electronics ◽

10.3390/electronics8121399 ◽

2019 ◽

Vol 8 (12) ◽

pp. 1399 ◽

Cited By ~ 4

Author(s):

Omar A. Saraereh ◽

Amer Alsaraira ◽

Imran Khan ◽

Peerapong Uthansakul

Keyword(s):

Resource Allocation ◽

Power Allocation ◽

Multiple Access ◽

Low Complexity ◽

System Capacity ◽

Resource Allocation Algorithm ◽

Allocation Algorithm ◽

User Grouping ◽

Power Domain ◽

Efficient Resource

Non-orthogonal multiple access (NOMA) has become the key technology in the future 5G wireless networks. It can achieve multi-user multiplexing in the transmit power domain by allocating different power, which can effectively improve the system capacity and spectral efficiency. Aiming at the problem of high computational complexity and improving system capacity in non-orthogonal multiple access (NOMA) based on orthogonal frequency division multiple access (OFDMA) for 5G wireless cellular networks, this paper proposes an improved low complexity radio resource allocation algorithm for user grouping and power allocation optimization. The optimization model is established with the goal of maximizing system capacity. Through the step-by-step optimization idea, the complex non-convex optimization problem is decomposed into two sub-problems to be solved separately. Firstly, all users are grouped based on the greedy method, and then the power allocation is performed on the sub-carriers of the fixed group. Simulation results show that the proposed algorithm has better system capacity than the existing state-of-the-art algorithms and reduced complexity performance.

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Interference Suppression and Resource Allocation Strategies Based on IoT Monitoring

International Journal of Circuits, Systems and Signal Processing ◽

10.46300/9106.2021.15.108 ◽

2021 ◽

Vol 15 ◽

pp. 1005-1014

Author(s):

Bin Wu ◽

Bingxin Yao ◽

Yin Yang ◽

Chaoran Zhou ◽

Ning Zhu

Keyword(s):

Resource Allocation ◽

Monitoring System ◽

Interference Suppression ◽

Monitoring Network ◽

Local Area ◽

Base Station ◽

System Capacity ◽

Monitoring Networks ◽

Resource Allocation Algorithm ◽

Allocation Strategies

The present application scenarios of the Internet of Things (IoT) often require the equipment to be adaptable, the resource allocation to be efficient, and the signal monitoring and transmission to be effective. However, the existing algorithms cannot solve the problem of system capacity reduction caused by the mutual interference between regions in data rates. Aiming at effectively improving the performance of the IoT monitoring system and ensuring the fairness of each monitoring terminal, this paper attempts to explore interference suppression and resource allocation strategies based on IoT monitoring. First, the paper established an IoT monitoring network model, and elaborated on interference suppression strategies for inter-layer interferences of “Macro Base Station (BS) – Micro Cells” and “Micro BS – Macro Cells” and for intra-layer interference that include the interference between local monitoring networks and interference between terminals in local area networks; then, the paper proposed a sub-carrier resource allocation scheme for IoT monitoring system with multiple inputs and outputs and a water-filling strategy of system channel power; at last, experimental results verified the effectiveness of the proposed interference suppression and resource allocation algorithm.

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