A different approach to finding the capacity of a Gaussian vector channel

A different approach to finding the capacity of a Gaussian vector channel The paper considers a Gaussian multiple-input multiple-output (MIMO) discrete-time vector channel with memory. The problem is to find the capacity of such a channel. It is known that the capacity of Gaussian vector channels with memory was given in [1]. In the present paper, we show a different approach, which uses another definition of the capacity. For a channel with n = 2 inputs and outputs, this approach gives an expression for the capacity which is different from that in [1]. The paper shows what the dependence of input signal components should be to give this capacity. A multidimensional water-filling interpretation works for the optimum vector input signal power distribution but cannot work for the description of the input component dependences. For the case of n ≥ 3 inputs and outputs, we give a lower bound on the channel capacity. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Problems of Information Transmission Springer Journals

A different approach to finding the capacity of a Gaussian vector channel

, Volume 42 (3) – Oct 18, 2006
14 pages

/lp/springer_journal/a-different-approach-to-finding-the-capacity-of-a-gaussian-vector-uheeaLSao7
Publisher
Nauka/Interperiodica
Subject
Engineering; Communications Engineering, Networks; Electrical Engineering; Information Storage and Retrieval; Systems Theory, Control
ISSN
0032-9460
eISSN
1608-3253
D.O.I.
10.1134/S0032946006030021
Publisher site
See Article on Publisher Site

Abstract

The paper considers a Gaussian multiple-input multiple-output (MIMO) discrete-time vector channel with memory. The problem is to find the capacity of such a channel. It is known that the capacity of Gaussian vector channels with memory was given in [1]. In the present paper, we show a different approach, which uses another definition of the capacity. For a channel with n = 2 inputs and outputs, this approach gives an expression for the capacity which is different from that in [1]. The paper shows what the dependence of input signal components should be to give this capacity. A multidimensional water-filling interpretation works for the optimum vector input signal power distribution but cannot work for the description of the input component dependences. For the case of n ≥ 3 inputs and outputs, we give a lower bound on the channel capacity.

Journal

Problems of Information TransmissionSpringer Journals

Published: Oct 18, 2006

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