In free-space optical satellite networks (FSOSNs), satellites connected via laser inter-satellite links (LISLs), latency is a critical factor, especially for long-distance inter-continental connections. Since satellit...
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In free-space optical satellite networks (FSOSNs), satellites connected via laser inter-satellite links (LISLs), latency is a critical factor, especially for long-distance inter-continental connections. Since satellites depend on solar panels for power supply, power consumption is also a vital factor. We investigate the minimization of total network latency (i.e., the sum of the network latencies of all inter-continental connections in a time slot) in a realistic model of a FSOSN, the latest version of the Starlink Phase 1 Version 3 constellation. We develop mathematical formulations of the total network latency over different LISL ranges and different satellite transmission power constraints for multiple simultaneous inter-continental connections. We use practical system models for calculating network latency and satellite optical link transmission power, and we formulate the problem as a binary integer linear program. The results reveal that, for satellite transmission power limits set at 0.5 W, 0.3 W, and 0.1 W, the average total network latency for all five inter-continental connections studied in this work levels off at 339 ms, 361 ms, and 542 ms, respectively. Furthermore, the corresponding LISL ranges required to achieve these average total network latency values are 4500 km, 3000 km, and 1731 km, respectively. Different limitations on satellite transmission power exhibit varying effects on average total network latency (over 100 time slots), and they also induce differing changes in the corresponding LISL ranges. In the absence of satellite transmission power constraints, as the LISL range extends from the minimum feasible range of 1575 km to the maximum feasible range of 5016 km, the average total network latency decreases from 589 ms to 311 ms.
The densification of small cell base stations in a 5G architecture is a promising approach to enhance the coverage area and facilitate the ever increasing capacity demand of end users. However, the bottleneck is an in...
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ISBN:
(纸本)9781509050192
The densification of small cell base stations in a 5G architecture is a promising approach to enhance the coverage area and facilitate the ever increasing capacity demand of end users. However, the bottleneck is an intelligent management of a backhaul/fronthaul network for these small cell base stations. This involves efficient association and placement of the backhaul hubs that connects these small-cells with the core network. Terrestrial hubs suffer from an inefficient non line of sight link limitations and unavailability of a proper infrastructure in an urban area. Realizing the popularity of flying platforms, we employ here an idea of using networked flying platform (NFP) such as unmanned aerial vehicles (UAVs), drones, unmanned balloons flying at different altitudes, as aerial backhaul hubs. The association problem of these NFP-hubs and small-cell base stations is formulated considering backhaul link and NFP related limitations such as maximum number of supported links and bandwidth. We then present an efficient and distributed solution of the designed problem, which performs a greedy search in order to maximize the sum rate of the overall network. A favorable performance is observed via a numerical comparison of our proposed method with optimal exhaustive search algorithm in terms of sum rate and run-time speed.
Wireless Sensor Networks (WSNs) have many characteristics that are attractive to a myriad of applications. In particular, nodes employ multi-hop communications to collaboratively forward sensed data back to one or mor...
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Wireless Sensor Networks (WSNs) have many characteristics that are attractive to a myriad of applications. In particular, nodes employ multi-hop communications to collaboratively forward sensed data back to one or more sinks. In this context, reducing the end-to-end delay between the sink and sensor/source nodes is of interest to many applications. In particular, those that require a fixed, upper bound on end-to-end delays. To this end, we focus on bounding the end-to-end delay from the sink to each source. We first formulate the problem as a binaryintegerprogram (BIP). As the problem is NP-hard, this paper proposes and studies two centralized, heuristic algorithms: Tabu and Domino. The key approach used by both algorithms is to determine the minimal number of extra wake-up slots required by a given network in order to ensure the delay of all end-to-end paths is within a given bound. We conducted two sets of experiments. The first set compares BIP, Tabu, and Domino in WSNs with up to 80 nodes. These experiments serve to compare the proposed algorithms against BIP, which become computationally expensive in large scale WSNs. The results show that, compared to BIP, the number of additional wake-up times generated by Tabu and Domino are within 5 and 10 % of the optimal solution. In the second set of experiments, which evaluates the algorithms in WSNs with 100-500 nodes, the average number of extra wake-up slots activated by Domino is 13 % greater than Tabu. These algorithms have a time complexity of and respectively, where is the number of nodes, is the number of slots in one period, and is the maximum number of iterations carried out by the Tabu algorithm.
In this paper, we study radio resource allocation (RRA) for multicasting in OFDMA based High Altitude Platforms (HAPs). We formulate an optimization problem for a scenario in which different sessions are multicasted t...
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ISBN:
(纸本)9781479928514
In this paper, we study radio resource allocation (RRA) for multicasting in OFDMA based High Altitude Platforms (HAPs). We formulate an optimization problem for a scenario in which different sessions are multicasted to user terminals (UTs) across HAP service area. We then solve it to find the best allocation of HAP resources such as radio power, sub-channels, and time slots. The objective is to maximize the number of UTs that receive the requested multicast streams in the HAP service area in a given OFDMA frame. The optimization problem comes out to be a Mixed integer Non-linearprogram (MINLP). Due to the high complexity of the problem and lack of special structures, we believe that breaking it into two easier subproblems and iterating between them to achieve convergence can lead to an acceptable solution. Subproblem 1 turns out to be a binary integer linear program (BILP) of no explicitly noticeable structure and therefore Lagrangian relaxation is used to dualize some constraints to get a BILP with some special structure that is easy to solve. The subgradient method is used to solve for the dual variables in the dual problem for three proposed methods to get the tightest bound in each. The obtained bounds can be used in a branch and bound (BnB) algorithm as its bounding subroutine at each node. Subproblem 2 turns out to be a simple linearprogram (LP) for which the simplex algorithm can be used to solve the subproblem to optimality. This paper focuses on subproblem 1 and its proposed solution techniques. In the results section of this paper, we compare the solution goodness for each method versus the well known bounding technique used in BnB which is linearprogram (LP) relaxation.
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