Abstract
Exploiting the benefits of multiple antenna technologies is strongly conditioned on knowledge of the wireless channel that affects the transmissions. To this end, various channel estimation algorithms have been proposed in the literature for multiple-input multiple-output (MIMO) channels. These algorithms are typically studied from a perspective that does not consider constraints on the energy consumption of their implementation. This article proposes a methodology for evaluating the total energy consumption required for transmitting, receiving, and processing a preamble signal in order to produce a channel estimate in multiple antenna systems. The methodology is used for finding the training signals that minimize the energy consumption for attaining given mean square estimation error. We show that the energy required for processing the preamble signal by executing the estimation algorithms dominates the total energy consumed by the channel estimation process. Therefore, algorithm simplicity is a key factor for achieving energy-efficient channel acquisition. We use our method for analyzing the widely used least squares and minimum mean square error (MSE) estimation algorithms and find that both have a similar energy consumption when the same MSE estimation is targeted.
Highlights
Multiple-input multiple-output (MIMO) communication techniques have been incorporated into different wireless systems due to their capability for allowing higher data rates or for increasing link reliability
We present a method for comparing the energy efficiency of different channel estimation algorithms
The energy consumption increases as a function of Np and Ptx has the same slope for minimum MSE (MMSE) and least squares (LS) estimation because k2 and k3 are equal in both cases
Summary
Multiple-input multiple-output (MIMO) communication techniques have been incorporated into different wireless systems due to their capability for allowing higher data rates (multiplexing gain) or for increasing link reliability (diversity gain). N=1 t=1 where Ts is the symbol period and Pel,tx = P DAC + Pfilter + Pmixer represents the power consumption of DAC, filters and mixer of each transmitter branch This model allows for each antenna to transmit a different and arbitrary sequences of training symbols, which can include silences. It is to be noted that the problem of channel estimation in a MIMO system with Nt transmit and Nr receive antennas is, in practice, a set of Nt independent single-input multiple-output problems, one per transmitter branch. Nr × Nt channel matrix H can be estimated sequentially by columns using a preamble in which only one antenna simultaneously transmits a training sequence, as shown in [7] (Figure 2) The energy consumption increases as a function of Np and Ptx has the same slope for MMSE and LS estimation because k2 and k3 are equal in both cases
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