In this study, the sum throughput maximisation problem for cognitive radio networks (CRNs) based on the multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) structure has been inve...
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In this study, the sum throughput maximisation problem for cognitive radio networks (CRNs) based on the multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) structure has been investigated. Hence, the intention is to maximise the downlink sum throughput of the CRN in a way that the sum power of the cognitive base station (CBS) remains below the given power limit and the induced interference on each subcarrier guarantees the interference threshold level predefined by primary users. Here, due to combinatorial constraints, the complex problem should be resolved. Hence, the core purpose of this study is to prepare a novel resource assignment algorithm that tries to fulfil these combinatorial constraints simultaneously. Therefore, this study makes progress towards solving the problem theoretically based on convex optimisation framework. An optimal solution has been implemented by proposing the iterative algorithm in which an optimal level of Lagrangian coefficients is obtained. Then, because of the optimal algorithm intricacy, the two low complicated algorithms are further suggested based on the solutions of two simplified versions of the original problem. Numerical results demonstrate that the suggested algorithms improve sum throughput considerably in comparison with classical algorithm. The proposed simplified algorithms converge to the optimal solutions' performance while their complexities are desirable for practical implementation.
On the basis of multi-layer satellite network, this paper presents a GEO/LEO double-layer satellite optical network structure that can meet the global all-weather coverage. Due to the limited number of antennas on the...
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ISBN:
(数字)9781510643628
ISBN:
(纸本)9781510643628
On the basis of multi-layer satellite network, this paper presents a GEO/LEO double-layer satellite optical network structure that can meet the global all-weather coverage. Due to the limited number of antennas on the satellite, the LEO satellites are divided into two categories according to the function. One of the categories, as cluster-head satellites, should both establish link with LEO satellites and GEO satellites. The cluster head satellites will also be grouped with the link distance as the index. Each group has the same number of satellites which communicate with the same GEO. A reasonable grouping method is used to avoid the problem of too many links being set up simultaneously with the same GEO satellite, which will affect the transmission delay and communication efficiency. In terms of route selection, the hop cost factor is introduced to improve the traditional KSP algorithm. Compared to the KSP algorithm at the cost of link distance, the designed algorithm limits the number of jumps during service transmission, so as to balance the link length and the number of hops well. Through MATLAB simulation, the proposed algorithm improves the efficiency of the utilization of inter-orbit link, reduces blocking rate, and makes the resourceallocation more reasonable.
This work presents a resource allocation algorithm that considers the characteristics of regular applications to choose the subset of processors, accelerators, and networks that minimize their parallel execution time ...
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This work presents a resource allocation algorithm that considers the characteristics of regular applications to choose the subset of processors, accelerators, and networks that minimize their parallel execution time in a small heterogeneous cluster environment. The resource allocation algorithm uses Heterogeneous Cluster Model (HCM) to estimate the execution time of the parallel applications. The experimental results have shown that, for applications with distinct behaviors, the resource allocation algorithm has successfully chosen the set of resources that minimizes their execution time.
This paper investigates the Device-to-Device (D2D) communications uplink resource allocation algorithm facing to arbitrary D2D pairs sharing subchannels with multiple cellular users (CUEs). Aiming to optimize the netw...
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ISBN:
(纸本)9781538635315
This paper investigates the Device-to-Device (D2D) communications uplink resource allocation algorithm facing to arbitrary D2D pairs sharing subchannels with multiple cellular users (CUEs). Aiming to optimize the network sum rate, the complexity is considerable due to the flexible interference relation. To reduce the complexity, the problem can be decomposed based on the time variance by two sub-problems: subchannel allocation and power allocation. For subchannel allocation, a clustering algorithm based on the hypergraph similarity of UEs is proposed, which constructs the D2D sharing set to enhance the clustering efficiency and conduces the complexity to be O(N-2). For power allocation, a bisection algorithm which can rapidly converge to the optimal solution is introduced to further promote the system throughput. Simulation results demonstrate that the proposed algorithm can achieve a superior sum rate performance compared to the conventional graph algorithm.
In indoor scenarios, visible light communication (VLC) access point (AP) can provide very high throughput and meet any illumination demands, while wireless fidelity (Wi-Fi) provides basic coverage in a large range. In...
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ISBN:
(纸本)9781509011445
In indoor scenarios, visible light communication (VLC) access point (AP) can provide very high throughput and meet any illumination demands, while wireless fidelity (Wi-Fi) provides basic coverage in a large range. In this paper, the downlink resourceallocation (RA) problem for hybrid VLC and Wi-Fi network is considered. A resource allocation algorithm combined with optical power dynamic allocation is proposed. The optimization goal is to maximize the Best Effort (BE) service users' aggregate throughput and users' proportional fairness under the premise of guaranteeing the minimum rate requirement of the Delay Constrained (DC) service users. Simulation results show that the algorithm we proposed is capable of achieving better performance in both aggregate throughput and individual fairness obviously when multi-user are extremely uneven distributed, compared with the algorithm under the condition of optical power average allocation.
The problem of frequency subchannels allocation between nodes in a common link is considered. It is assumed that every node has an access to a limited subset of subchannels and its requirements to a data rate is known...
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ISBN:
(纸本)9781479940509
The problem of frequency subchannels allocation between nodes in a common link is considered. It is assumed that every node has an access to a limited subset of subchannels and its requirements to a data rate is known. Under these conditions, subchannels allocationalgorithm is proposed.
resourceallocation management is the key issue to improve the performance of visible light communication (VLC) / WiFi hybrid network. This paper proposes an improved resource allocation algorithm based on proportiona...
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ISBN:
(数字)9781510646384
ISBN:
(纸本)9781510646384;9781510646377
resourceallocation management is the key issue to improve the performance of visible light communication (VLC) / WiFi hybrid network. This paper proposes an improved resource allocation algorithm based on proportional fairness (PF) algorithm. Its main idea is to compensate users, and then establish a VLC / WiFi hybrid network model to simulate the traditional algorithm and the improved algorithm respectively, It is verified that the improved algorithm has better fairness and higher throughput than the traditional algorithm.
Aiming at the problem that the location of the secondary base station affects the interference between the primary and secondary systems directly and the reasonable allocation of channel resources, an Internet of Thin...
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Aiming at the problem that the location of the secondary base station affects the interference between the primary and secondary systems directly and the reasonable allocation of channel resources, an Internet of Things (IoT) sensor network resourceallocation scheme using an improved chaotic firefly algorithm is proposed. This solution builds a multi-objective optimization model based on interference analysis of the working scenario of the cognitive radio. The goal is to protect the primary user's normal activity to maximize the throughput of the secondary system and maximize the number of users that can be covered by the secondary base station. Because the multi-objective model is a non-linear convex optimization problem, the paper uses an improved chaotic firefly algorithm to solve it. Chaos algorithm is introduced into the firefly algorithm. By perturbing individuals, the convergence speed is accelerated and the probability of local optimization is reduced. The algorithm can efficiently obtain the optimal solution while reducing the complexity of the problem. The simulation results show that the method proposed in this paper can optimize the performance of the secondary system while guaranteeing the priority of the primary user. And it is superior to several advanced algorithms.
Energy-efficient scheduling and resourceallocation strategies help reduce interference and extend the lifetime of power-limited Internet of Things (IoT) devices. This paper focuses on improving the transmission effic...
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ISBN:
(纸本)9798350336672
Energy-efficient scheduling and resourceallocation strategies help reduce interference and extend the lifetime of power-limited Internet of Things (IoT) devices. This paper focuses on improving the transmission efficiency and working time of power-limited data acquisition equipment, e.g., low-power consumption IoT sensors. In particular, the cognitive device tunes its transmission time and power rationally to avoid interference and recharges itself by conducting energy harvesting. Inspired by the concept of the age of information, we coin the concept of the value of update (VoU) and use it to guide devices to upload data in a timely manner and optimize the key parameters through a deep deterministic policy gradient (DDPG) neural network to maximize the long-term VoU. Finally, extensive simulations are conducted to demonstrate the effectiveness and robustness of the proposed scheme.
resourceallocation is a key technology of cloud *** present,the most of studies on resourceallocation mainly focus on improving the overall performance by balancing the load of data *** paper will design the experim...
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resourceallocation is a key technology of cloud *** present,the most of studies on resourceallocation mainly focus on improving the overall performance by balancing the load of data *** paper will design the experimental platform of resource allocation algorithm,energy optimization and performance analysis,obtain original achievements in scientific research,for the resourceallocation method based on immune algorithm and energy optimization in cloud computing to provide innovative ideas and scientific *** research has important significance for further study on resourceallocation and energy optimization in cloud computing environment.
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