Robust time-of-arrival estimation in multipath channels with OFDM signals

Abstract

Abstract-Time-of-arrival (TOA) estimation of OFDM signals in multipath channels is challenging, especially when the signal bandwidth is limited, such as is the case of WIFI. In this paper, a novel low complexity TOA estimation algorithm is developed for OFDM signals that is robust to various multipath environments. We approximate the received signal as Gaussian with a proposed autocorrelation model, and then derive the Maximum Likelihood estimator with an efficient implementation algorithm. The estimator performance was tested with off-theshelf WIFI 802.11g routers. The results show that the proposed TOA estimator outperforms other known reference methods over various indoor environments.

ToA-based Iterative Localization in Rich Multipath Channels

“…where γ τ k is the vector composed by the diagonal elements of Γ τ k and C = R H k DR k with R k = diag {r k }. It is shown in [6] that (17) can be efficiently computed for all the delays on the search grid as:…”

“…To determine the co-variance matrix Σ x k , we assume similarly to [6] the multipath arrivals to be confined to a finite grid with a sufficiently fine resolution ∆. Under this assumption, x k can be expressed by:…”

“…This subspace method uses an estimation of the signal autocorrelation which requires a large number of independent signal observations with the same time-ofarrival. Papers [6], [7] rather rely on the central limit theorem for random vectors to formulate an approximate Maximum Likelihood delay estimator in dense multipath. Given some prior knowledge on the shape of the channel power delay profile, this approach is shown to outperform super-resolution and GML methods in practical environments [6].…”

“…In this paper, we will use the DPE method developed in [9]. This method relies on the same approximate Maximum Likelihood formulation as papers [6] and [7] and requires some prior knowledge on the shape of the channel power delay profile (PDP).…”

“…In this paper, we therefore propose to extend the iterative localization method of [10] to be able to operate in a rich multipath environment, typical of dense urban and indoor environments. We resort to the approach developed in [6], [7] to estimate the propagation delay of the signal using some prior knowledge of the channel PDP.…”