Full-dimension multiple-input multiple-output (FD-MIMO) systems, in which base stations are equipped with a large number of antennas in a two-dimensional panel, has received considerable attention from academia resear...
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Full-dimension multiple-input multiple-output (FD-MIMO) systems, in which base stations are equipped with a large number of antennas in a two-dimensional panel, has received considerable attention from academia researchers and industry practitioners. Compared with legacy cellular communication systems, FD-MIMO systems can achieve significantly higher spectral efficiency with high order multi-user MIMO (MU-MIMO) transmissions. However, as high-order MU-MIMO also incurs high precoding and scheduling complexity, it is critical to reduce complexity of these operations in order to realize throughput potential of FD-MIMO systems in practice. In this paper, we propose a reduced complexity algorithm to realize the high performance precoding technique, signal-to-leakage plus noise ratio (SLNR) precoding, and propose an efficient scheduling algorithm to enable high-order MU-MIMO transmissions in FD-MIMO systems. We further demonstrate the effectiveness of the proposed algorithms by using system level simulations.
The deployment of femto-cells in fifth-generation (5G) systems is necessary thanks to their advantages in terms of the number of supported users, and the reduction of energy consumption, thus it's promising to ado...
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ISBN:
(纸本)9781538681749;9781538681732
The deployment of femto-cells in fifth-generation (5G) systems is necessary thanks to their advantages in terms of the number of supported users, and the reduction of energy consumption, thus it's promising to adopt this concept to meet the 5G networks' requirements. However, the allocation of resources and the management of traffic while maintaining the quality of service (QoS); constitutes a major challenge in terms of fairness and perceived throughput at the terminal *** this paper, a number of scheduling algorithms planned to be used in 5G, namely the Proportional Fair (PF) algorithm, the Exponential Proportional Fair algorithm (EXP / PF) and the algorithm Maximum Largest Weighted Delay First (MLWDF) are studied and compared in terms of equity (Fairness Index), useful rate (Goodput) and spectral efficiency, at the level of femto-cells in the downward direction.
This paper considers efficient and low complexity multiuser scheduling algorithms for the uplink multiple-input multiple-output systems. The exhaustive search algorithm (ESA) that gives the optimal performance, howeve...
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ISBN:
(纸本)9781457701009
This paper considers efficient and low complexity multiuser scheduling algorithms for the uplink multiple-input multiple-output systems. The exhaustive search algorithm (ESA) that gives the optimal performance, however, is complexity prohibitive for practical implementation. Aiming at reducing the complexity while keeping the achievable sum rate performance, two heuristic algorithms are proposed for the multiuser scheduling problem: the improved genetic algorithm and simplified norm-based greedy algorithm. Numerical examples demonstrate that our proposed scheduling algorithms perform close to the optimal ESA, while with much lower complexity.
The exponential rise in the use of IoT devices has produced a growing risk of Denial of Service (DoS) attacks on IoT infrastructure. DoS attacks can prevent critical services from reaching legitimate users by targetin...
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ISBN:
(数字)9798350309652
ISBN:
(纸本)9798350309669
The exponential rise in the use of IoT devices has produced a growing risk of Denial of Service (DoS) attacks on IoT infrastructure. DoS attacks can prevent critical services from reaching legitimate users by targeting communication protocols such as Message Queuing Telemetry Transport (MQTT). Prior research has touched on algorithms to detect DoS attacks on the MQTT protocol, but the discussion of broker recovery from DoS attacks is not prevalent in the literature. This paper proposes the use and adaptation of efficient scheduling algorithms for minimizing tardy processing time to enhance the on-time delivery of backed-up queries to MQTT brokers following DoS attacks.
Mobile crowd computing (MCC) has emerged as a promising paradigm to leverage the underutilised computational resources of smart mobile devices (SMDs). However, the energy constraints of these devices pose a significan...
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ISBN:
(数字)9798350370249
ISBN:
(纸本)9798350370270
Mobile crowd computing (MCC) has emerged as a promising paradigm to leverage the underutilised computational resources of smart mobile devices (SMDs). However, the energy constraints of these devices pose a significant challenge in efficiently executing computational tasks. This study analyses the energy efficiency of various scheduling algorithms for MCC environments. The study compares the performance of seven scheduling algorithms: PPIA, RAS, PSO, GA, MaxMin, MinMin, and MCT. These algorithms were evaluated in terms of their energy efficiency when executing different sets of tasks with varied instruction lengths. The experiment used a simulated MCC environment with real data from five SMDs. The results demonstrate that the PSO algorithm consistently outperformed the other scheduling schemes regarding energy efficiency across all task sets. The GA algorithm also showed promising results. The MinMin algorithm exhibited the lowest energy efficiency. The findings of this study provide valuable insights for designing and implementing energy-efficient task scheduling strategies in MCC systems. Analysing the different algorithms under varying task loads can help MCC service providers make informed decisions when selecting appropriate scheduling techniques to optimise the energy utilisation of SMDs.
Wireless navigation networks enable location-awareness in GPS-challenged environments. For such networks, scheduling algorithms are needed to improve the navigation accuracy through measurement pair selections under l...
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ISBN:
(纸本)9781479913510
Wireless navigation networks enable location-awareness in GPS-challenged environments. For such networks, scheduling algorithms are needed to improve the navigation accuracy through measurement pair selections under limited communication resource. In this paper, we develop an analytical framework to determine the location error evolution for different scheduling algorithms and network settings. Under this framework, we provide sufficient conditions for the stability of the location error evolution, and we quantify the time-averaged network location errors (NLEs) for scheduling algorithms with and without exploiting the network states. Furthermore, we show the optimality of the proposed scheduling algorithms in terms of the error scaling with respect to the agent density. These results provide fundamental insights into the effects of scheduling algorithms and network settings on the location error evolution, leading to efficient scheduling algorithms for navigation networks.
Cloud computing is a new paradigm in computing that enables the availability of various resources at one place on the user's demand. In cloud computing, a cloud is a unit containing various resources like hardware...
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ISBN:
(纸本)9781665447874
Cloud computing is a new paradigm in computing that enables the availability of various resources at one place on the user's demand. In cloud computing, a cloud is a unit containing various resources like hardware, software, etc. In contrast, computing refers to the way or mechanism to access the available resources from the cloud. Numerous challenges such as cloud security, performance, task scheduling etc., are observed during the adaption of cloud computing. Task scheduling aims at the optimized resource allocation to the various tasks. The performance of any system is directly dependent on the scheduling process. More effective task scheduling will undoubtedly lead to the high performance of the system. This paper highlights the various task scheduling algorithms and their advantages and disadvantages in the cloud environment. Further, A novel effort is made to categorize existing task scheduling algorithms based on their working concepts.
Reducing energy consumption over mobile networks and devices is an important and challenging issue. On the one hand, power is a limited resource on mobile devices and its usage should be optimized. On the other hand, ...
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Reducing energy consumption over mobile networks and devices is an important and challenging issue. On the one hand, power is a limited resource on mobile devices and its usage should be optimized. On the other hand, energy consumption constitutes an important item within operating expenditure (OPEX) for network providers. In the literature, many studies are dedicated to evaluate scheduling mechanisms from the energy consumption perspective. However, most of these only consider few well known schemes such as Proportional Fair, Best-CQI and Round Robin. In the paper, we extend these studies to include new promising scheduling techniques such as PF, EXP-PF and MLWDF algorithm. In addition, we consider multiple metrics related to QoS, energy and fairness. Performance results show that MLWDF is more energy efficient than EXP-PF and PF schemes while providing better QoS for users.
In wireless sensor networks, some sensor nodes can switch to a sleep state to conserve energy if their neighbors can provide similar sensing coverage. In reality, when more sensor nodes sleep, a sensor network's c...
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ISBN:
(纸本)9781479931897
In wireless sensor networks, some sensor nodes can switch to a sleep state to conserve energy if their neighbors can provide similar sensing coverage. In reality, when more sensor nodes sleep, a sensor network's coverage may degrade. In this paper, we evaluate the coverage-aware sleep scheduling algorithm in areas with uneven event distributions and study its performance on event detection rate and event detection delay. There are two major improvements in this paper: first, we add the components of event generator into this paper and collect data on event detection rate and event detection delay. Second, we analyze sleep probability and energy consumption for coverage-aware sleep scheduling algorithm. Compared with randomized deployment strategy, the density adaptive deployment performs better on event detection delay and event detection rate.
In this paper, we propose a new scheduling algorithm for IEEE802.16 Broadband wireless Metropolitan Area Networks in TDD mode. Based on some known algorithms such as Modified Deficit Round Robin (MDRR), Proportional F...
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In this paper, we propose a new scheduling algorithm for IEEE802.16 Broadband wireless Metropolitan Area Networks in TDD mode. Based on some known algorithms such as Modified Deficit Round Robin (MDRR), Proportional Fairness (PF) and Adaptive Proportional Fairness (APF), we have studied the scheduling problem and proposed scheduling algorithm, called (Enhanced-APF) for focuses on an efficient mechanism to serve high priority traffic in order to perform and achieve high resource utilization in the Wimax Base Station. We give a detailed simulation study for the proposed scheduling algorithm and its performance has been compared. Based on OPNET modeler Simulation, results show that the proposed algorithm can increase the network throughput, maintain relative fairness, and lower delay of dealing with different requirements from users under congestion conditions.
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