Abstract
In this paper, we propose various localization error optimal beamforming strategies and subsequently study the trade-off between data and localization services while budgeting time and frequency resources in a multi-user millimeter-wave framework. Allocating more resources for the data service phase instead of localization would imply higher data rate but, concurrently, also a higher position and orientation estimation error. In order to characterize this trade-off, we firstly derive a flexible application-dependent localization error cost function combining the Cramer-Rao lower bounds of delay, angle of departure and/or angle of arrival estimates at a mobile receiver over the downlink. Consequently we devise different fairness criteria based localization error optimal beamforming strategies in a multi-user context. Finally, we show the advantage of the latter beamforming strategies and assess the communication-localization trade-off with respect to various time-frequency resource division schemes.
Highlights
An exponential increase in the demand for low latency high data rate services is driving the wireless communication industry into adopting high frequency millimeter wave as a key technology in the 5th generation (5G) of cellular networks [1]
In this paper, we propose various localization error optimal beamforming strategies and subsequently study the trade-off between data and localization services while budgeting time and frequency resources in a multi-user millimeter-wave framework
We look at the resulting average performance per user while considering data rate, position estimation error bounds (PEB) and orientation estimation error bounds (OEB)
Summary
An exponential increase in the demand for low latency high data rate services is driving the wireless communication industry into adopting high frequency millimeter wave (mmWave) as a key technology in the 5th generation (5G) of cellular networks [1]. In [9] the authors characterize the CRLB for the same location-dependent estimation variables, but within multi-carrier systems Using these theoretical performance bounds, recent works in the literature have been dedicated towards finding the localization optimal beamformers. We study different resource budgeting strategies in a framework consisting of both communication and localization services for multi-user cases in a multi-carrier system. For this purpose, we first derive the localization optimal beamformers and recall the communication oriented optimal beamfomers for both single and multiple users from [21].
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