Maximizing Weighted Sum-Rate Over Gaussian Broadcast Channels

A power assignment over Gaussian broadcast channels splits the power budget at the access point among all user-channel pairs subject to per-channel upper-bounds on the sum-power, and is optimal if it maximizes the weighted sum-rate (WSR). In this paper we first present a geometric algorithm for comp...

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Vydáno v:IEEE transactions on information theory Ročník 70; číslo 4; s. 2922 - 2935
Hlavní autoři: Wan, Peng-Jun, Chen, Pengpeng
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.04.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Broadcasting
Budgets
Channels
Complexity
Complexity theory
Computation
convex hull
Costs
Encoding
Geometric algorithms
Heuristic algorithms
Interference cancellation
NOMA
Optimization
power assignment
Time complexity
Upper bounds
water-filling
Weighted sum-rate
ISSN:0018-9448, 1557-9654
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Shrnutí:A power assignment over Gaussian broadcast channels splits the power budget at the access point among all user-channel pairs subject to per-channel upper-bounds on the sum-power, and is optimal if it maximizes the weighted sum-rate (WSR). In this paper we first present a geometric algorithm for computing an optimal power assignment over single Gaussian broadcast channel, which has linear complexity if all users are presorted either by weight or by noise. We also provide an intuitively appealing water-filling interpretation of this geometric algorithm. By leveraging such water-filling interpretation, we develop a water-filling algorithm for computing an optimal power assignment over parallel Gaussian broadcast channels, whose complexity is linear in the number of user-channel pairs if all users are presorted by weight. From these algorithmic studies, we derive clean and simple expressions of the maximum WSR in both integral forms and sum forms. By exploiting the rich property of those forms, we further give a linear-complexity algorithm for computing a power budget at the access point, subject to a given upper bound, which maximizes the difference between the maximum WSR and a linear cost of the power budget. The algorithmic studies in this paper also reveal that a single Gaussian broadcast channel can be decomposed into parallel Gaussian single-user channels which preserve the maximum WSR.
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ISSN:0018-9448
1557-9654
DOI:10.1109/TIT.2023.3312134