Optimum antenna configurations for millimetre-wave communications from high-altitude platforms

Pearce, D.A.J.; Grace, David

doi:10.1049/iet-com:20050077

Cited by 5 publications

(5 citation statements)

References 6 publications

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“…d S su is the distance between BS s in tier S and user u. In 1, the first factor C/4πd S su f S c 2 captures propagation and path-loss and the second A S su is the attenuation gain due to environment effects which depends on the distance between the BS s and user u and given as [15], [21]:…”

Section: ) Front-hauling Channel Modelmentioning

confidence: 99%

“…In this case, inter-cell interference is assumed to be I M mu = 0 due to large distances between users that using the same frequency bands in the ground tier. Hence, the association problem is linear and we can omit constraint (21). On the other hand, the edge users can be served by the HAPs and satellite station as shown in Fig 3. Hence, (22) becomes a convex function with respect to P S su,n .…”

Section: B Low Complexity Solutionmentioning

confidence: 99%

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Improvement of the Global Connectivity Using Integrated Satellite-Airborne-Terrestrial Networks With Resource Optimization

Alsharoa

Alouini

2020

IEEE Trans. Wireless Commun.

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In this paper, we propose a novel wireless scheme that integrates satellite, airborne, and terrestrial networks aiming to support ground users. More specifically, we study the enhancement of the achievable users' throughput assisted with terrestrial base stations, high altitude platforms (HAPs), and satellite station. The goal is to optimize the resource allocations and the HAPs' locations in order to maximize the users' throughput. In this context, we propose to solve the optimization problem in two stages; first a short-term stage and then a long-term stage. In the short-term stage, we start by proposing a near optimal solution and low complexity solution to solve the associations and power allocations. In the first solution, we formulate and solve a binary linear optimization problem to find the best associations and then using Taylor expansion approximation to optimally determine the power allocations. While in the second solution, we propose a low complexity approach based on frequency partitioning technique to solve the associations and power allocations. One the other hand, in the long-term stage, we optimize the locations of the HAPs by proposing an efficient algorithm based on a recursive shrink-and-realign process. Finally, selected numerical results show the advantages provided by our proposed optimization scheme.

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Section: ) Front-hauling Channel Modelmentioning

confidence: 99%

Section: B Low Complexity Solutionmentioning

confidence: 99%

Improvement of the Global Connectivity Using Integrated Satellite-Airborne-Terrestrial Networks With Resource Optimization

Alsharoa

Alouini

2020

IEEE Trans. Wireless Commun.

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“…The channel gains g i,k,c,t depend upon the instantaneous values of large scale fading and small scale fading. In a HAP system, large scale fading is a result of free space path loss and attenuation due to rain and clouds [29]. Small scale fading is acceptably modeled as Ricean fading due to the presence of line of sight rays from the HAP to most of the locations in the HAP service area [1].…”

Section: Scope and Contribution Of The Papermentioning

confidence: 99%

“…(4) in this paper and (13), (14) and (15) from our earlier work in [24]. The channel consists of a free space pathloss propagation model, Ricean fading as suggested in [1], the rain attenuation model in [29], the HAP aperture antenna model in [21] and parabolic reflector user antennas. In the simulation, the user positions change during every iteration according to a uniform probability distribution about the HAP footprint centers.…”

mentioning

confidence: 99%

Optimizing radio resources for multicasting on high-altitude platforms

Ibrahim

Alfa

2019

J Wireless Com Network

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High-altitude platforms (HAPs) are quasi-stationary aerial wireless communications platforms meant to be located in the stratosphere, to provide wireless communications and broadband services. They have the ability to fly on demand to temporarily or permanently serve regions with unavailable infrastructure. In this paper, we consider the development of an efficient method for resource allocation and controlling user admissions to multicast groups in a HAP system. Power, frequency, space and time domains are considered in the problem. The combination of these many aspects of the problem in multicasting over an OFDMA HAP system were not, to the best of our knowledge, addressed before. Due to the strong dependence of the total number of users that could join different multicast groups on the possible ways we may allocate resources to the different multicast groups, it is important to consider a joint user to multicast group assignments and radio resource management across the groups. From the service provider's point of view, it would be in its best interest to be able to admit as many users as possible, while satisfying their quality of service requirements. The problem turns out to be a mixed integer non-convex non-linear program for which branch and bound solution framework is guaranteed to solve the problem. Branch and bound (BnB) can be also used to obtain sub-optimal solutions with desired quality. Even though branch and bound is guaranteed to find the optimal solution, the computational cost could be extremely high, which is why we considered different types of enhancements to BnB. Mainly, we consider reformulations by linearizing a specific set of quadratic constraints in the derived formulation, as well as the application of different branching techniques to find the one that performs the best. Based on the conducted numerical experiments, it was concluded that linearization, applied for at least 100 presolving rounds, and cloud branching achieve the best performance.

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“…The channel gains depend upon the instantaneous values of large scale fading and small scale fading. In a HAP system, large scale fading is a result of free space path loss and attenuation due to rain and clouds [18]. Small scale fading is acceptably modeled as Ricean fading due to the presence of line of sight rays from the HAP to most of the locations in the HAP service area [19].…”

Section: System Modelmentioning

confidence: 99%

Using Lagrangian Relaxation for Radio Resource Allocation in High Altitude Platforms

Ibrahim

Alfa

2015

IEEE Trans. Wireless Commun.

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Abstract-In this paper, we study radio resource allocation for multicasting in OFDMA based high altitude platforms (HAPs). We formulate and solve an optimization problem that finds the best allocation of HAP resources such as radio power, subchannels, and time slots. The problem also finds the best possible frequency reuse across the cells that constitute the service area of the HAP. The objective is to maximize the number of user terminals that receive the requested multicast streams in the HAP service area in a given OFDMA frame. A bounding subroutine in a branch and bound algorithm can be obtained by decomposing it into two easier subproblems, due to its high complexity, and solving them iteratively. Subproblem 1 turns out to be a binary integer linear program of no explicitly noticeable structure and therefore Lagrangian relaxation is used to dualize some constraints to get a structure that is easy to solve. Subproblem 2 turns out to be a linear program with a continuous knapsack problem structure. Hence a greedy algorithm is proposed to solve subproblem 2 to optimality. The subgradient method is used to solve for the dual variables in the dual problem to get the tightest bounds.

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Optimum antenna configurations for millimetre-wave communications from high-altitude platforms

Cited by 5 publications

References 6 publications

Improvement of the Global Connectivity Using Integrated Satellite-Airborne-Terrestrial Networks With Resource Optimization

Improvement of the Global Connectivity Using Integrated Satellite-Airborne-Terrestrial Networks With Resource Optimization

Optimizing radio resources for multicasting on high-altitude platforms

Using Lagrangian Relaxation for Radio Resource Allocation in High Altitude Platforms

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