Pilot-Based Channel Estimation for OFDM Systems by Tracking the Delay-Subspace

Abstract

Abstract-In orthogonal frequency division multiplexing (OFDM) systems over fast-varying fading channels, channel estimation and tracking is generally carried out by transmitting known pilot symbols in given positions of the frequency-time grid. The traditional approach consists of two steps. First, the least-squares (LS) estimate is obtained over the pilot subcarriers. Then, this preliminary estimate is interpolated/smoothed over the entire frequency-time grid. In this paper, we propose to add an intermediate step, whose purpose is to increase the accuracy of the estimate over the pilot subcarriers. The presented techniques are based on the observation that the wireless radio channel can be parametrized as a combination of paths, each characterized by a delay and a complex amplitude. The amplitudes show fast temporal variations due to the mobility of terminals while the delays (and their associated delay-subspace) are almost constant over a large number of OFDM symbols. We propose to track the delay-subspace by a subspace tracking algorithm and the amplitudes by the least mean square algorithm (or modifications of the latter). The approach can be extended to multiple input multiple output OFDM or multicarrier code-division multiple-access systems. Analytical results and simulations prove the relevant benefits of the novel structure.Index Terms-Channel estimation, fading radio channel, multiple input multiple output (MIMO), orthogonal frequency-division multiplexing (OFDM), subspace tracking.

Adaptive OFDM synchronization using quadratic search step sizes

“…When the algorithm is tracking small changes in the STO (i.e., s = 1), only the cost functions of adjacent STO estimates are evaluated, so only 3(N cp +2) complex multiplications are performed. In the rare occurrence of large changes in STO, the algorithm can perform up to 3(3N cp ) = 9N cp complex multiplications since the sets of STO estimates As mentioned in [5], since the STO varies slowly with time, changes in the STO are somewhat rare events that occur on the order of hundreds of symbols, so the computational complexity of the proposed estimator is approximately a factor of 3(N cp +2) / 3(N+N cp ) = (N cp +2) / (N+N cp ) of the non-adaptive estimator. For the OFDM signal specifications given in Table I, this factor is (16+2) / (64+16) = 0.225 for IEEE 802.11a and (10+2) / (128+10) = 0.087 for the smallest bandwidth LTE signal.…”

Parametric Channel Estimation for Pseudo-Random User-Allocation in Uplink OFDMA

“…Differing from [8] is the incorporation of the new information into the matrix. In (13), we have used linear averaging, in which the effect of a new symbol decreases with time, as opposed to applying a constant weight to the new value as in [8].…”

“…In (13), we have used linear averaging, in which the effect of a new symbol decreases with time, as opposed to applying a constant weight to the new value as in [8]. The reason for this, is that in a multi-user environment, the allocation scheme changes very rapidly, and hence the entire duration of the algorithm is several tens of OFDM symbols.…”

“…Once the subspace tracking algorithm converges, the number of paths are estimated (L) using the method given in [8] and delay subspace basis is derived as…”

Improving the chromatic dispersion tolerance in long-haul fibre links using the coherent optical orthogonal frequency division multiplexing

“…The outputs of DACs are passed through a serial -parallel module prior to removing the CP. Owing to the CP, the linear convolution between the transmitted signal and the channel becomes a circular convolution; hence, the output of the FFT can be written as a product in the matrix form given by [21] …”