Small cell networks: Speed based power allocation

Kavitha, Veeraruna; Capdevielle, Véronique; Gupta, Manu K.

doi:10.1109/allerton.2013.6736688

Cited by 1 publication

(4 citation statements)

References 15 publications

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“…Note that service requirements S is independent of Z = (H O , V ). Hence, using equation (13) and equations (26)-(30) and conditioning on Z, the average of the overall service time equals the equation (14).…”

Section: Expected Overall Service Time Bmentioning

confidence: 99%

“…At any given time, the rates chosen are less than the "maximal" transmission rate (capacity) at that time. Parts of this work were presented in [14]. In this paper, we generalized the set of rates and more importantly included the system level simulator.…”

Section: Introductionmentioning

confidence: 99%

“…The more the choices, the finer is the control and better would be the improvement in performance. In [14], we assumed that system supports N choices and the set of these choices is different for different speeds. In this paper, using the system level simulator, we also include a study with a common (possibly bigger) set of rate choices.…”

Section: Introductionmentioning

confidence: 99%

“…But this is a coarse (small or macro BS) control, which may not improve the performance significantly. Parts of this work were presented in [14]. In this paper, we generalized the set of rates and more importantly included the system level simulator.…”

Section: Introductionmentioning

confidence: 99%

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Speed based optimal power control in small cell networks

Kavitha

Gupta

Capdevielle

et al. 2019

Computer Communications

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Small cell networks promise good quality of service (QoS) even for cell edge users, however pose challenges to cater to the high-speed users. The major difficulty being that of frequent handovers and the corresponding handover losses, which significantly depend upon the speed of the user. It was shown previously that the optimal cell size increases with speed. Thus, in scenarios with diverse users (speeds spanning over large ranges), it would be inefficient to serve all users using common cell radius and it is practically infeasible to design different cell sizes for different speeds. Alternatively, we propose to allocate power to a user based on its speed, e.g., higher power virtually increases the cell size. We solve well known Hamiltonian Jacobi equations under certain assumptions to obtain a power law, optimal for load factor and busy probability, for any given average power constraint and cell size. The optimal power control turns out to be linear in speed. We build a system level simulator for small cell network, using elaborate Monte-Carlo simulations, and show that the performance of the system improves significantly with linear power law. The power law is tested even for the cases, for which the system does not satisfy the assumptions required by the theory. For example, the linear power law has significant improvement in comparison with the 'equal power' system, even in presence of time varying and random interference. We observe good improvement in almost all cases with improvements up to 89% for certain configurations.

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Section: Expected Overall Service Time Bmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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