Performance limits of channel parameter estimation for joint communication and positioning

Abstract

Recently, a system concept for joint communication and positioning has been proposed by the authors. Channel parameter estimation (CPE) is the core part of this system proposal. Parameters of the physical channel, which can be exploited for positioning, are estimated based on the assumption that a priori knowledge about pulse shaping and receive filtering is available. At the same time, channel estimates of the equivalent discrete-time channel model, which are needed for data detection, are obtained inherently. This article focusses on the positioning part of the system proposal. Performance limits for CPE in terms of Cramer-Rao lower bounds are determined for different channel models. The influence of oversampling and of different channel characteristics is investigated. Oversampling proves especially helpful in dense multipath scenarios, which are most challenging. Based on the presented results, oversampling with a factor of two is recommended in order to improve the positioning accuracy. Excessive oversampling like in conventional global positioning system receivers is not necessary.

Semi-blind channel estimation for joint communication and positioning

“…obtained similar as is [13], [14]. Note that the CRLB is only valid in the high SNR regime for M ≥ 2, since the estimator Fig.…”

Simultaneous Model and Parameter Estimation for Joint Communication and Positioning

“…The second reason for not further investigating the ESPRIT method in this framework in this contribution is the ESPRITS's algorithm's requirement of oversampling in the signal model. For the proposed joint communication and positioning system the effect of oversampling was studied and discussed in depth in [51], [52] and the authors concluded that the achievable gain for the positioning side of the system is most pronounced for an increase from no oversampling to J = 1, to J = 2. On the other hand, for the communication side of the system, J = 1 already yields sufficient statistics and therefore oversampling for the communication side entails a huge complexity without improving the bit error rate performance.…”

Joint maximum likelihood time-delay estimation for LTE positioning in multipath channels

“…However, it is also the most complex model because of the many unknowns to estimate. Despite its complexity, this estimation model has been widely studied, for instance, with super-resolution techniques in [9,10], with the ML criterion in [11], or in a two-step approach in [12]. On the other hand, channel estimation models can be simplified by defining equispaced or periodic taps relative to the time delay of the first path.…”