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Asymptotically Optimal Water-Filling in Vector Multiple-Access Channels (2001)
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| Venue: | IEEE Trans. Inform. Theory |
| Citations: | 80 - 4 self |
BibTeX
@ARTICLE{Viswanath01asymptoticallyoptimal,
author = {Pramod Viswanath and David N. C. Tse and Venkat Anantharam},
title = {Asymptotically Optimal Water-Filling in Vector Multiple-Access Channels},
journal = {IEEE Trans. Inform. Theory},
year = {2001},
volume = {47},
pages = {241--267}
}
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Abstract
Dynamic resource allocation is an important means to increase the sum capacity of fading multiple-access channels (MACs). In this paper, we consider vector multiaccess channels (channels where each user has multiple degrees of freedom) and study the effect of power allocation as a function of the channel state on the sum capacity (or spectral efficiency) defined as the maximum sum of rates of users per unit degree of freedom at which the users can jointly transmit reliably, in an information -theoretic sense, assuming random directions of received signal. Direct-sequence code-division multiple-access (DS-CDMA) channels and MACs with multiple antennas at the receiver are two systems that fall under the purview of our model. Our main result is the identification of a simple dynamic power-allocation scheme that is optimal in a large system, i.e., with a large number of users and a correspondingly large number of degrees of freedom. A key feature of this policy is that, for any user, it depends on the instantaneous amplitude of channel state of that user alone and the structure of the policy is "water-filling." In the context of DS-CDMA and in the special case of no fading, the asymptotically optimal power policy of water-filling simplifies to constant power allocation over all realizations of signature sequences; this result verifies the conjecture made in [28]. We study the behavior of the asymptotically optimal water-filling policy in various regimes of number of users per unit degree of freedom and signal-to-noise ratio (SNR). We also generalize this result to multiple classes, i.e., the situation when users in different classes have different average power constraints.
Keyphrases
vector multiple-access channel optimal water-filling large number channel state unit degree sum capacity direct-sequence code-division multiple-access multiple-access channel maximum sum power allocation water-filling simplifies main result constant power allocation multiple antenna special case key feature information theoretic sense multiple degree optimal water-filling policy vector multiaccess channel optimal power policy simple dynamic power-allocation scheme random direction signature sequence signal-to-noise ratio different average power constraint various regime spectral efficiency different class large system important mean instantaneous amplitude dynamic resource allocation
