AI & ML
Angle Estimation for Initial Access in True-Time-Delay Systems: Communication and Sensing Tradeoff
arXiv eess.SP0 views
arXiv:2611.07911v1 Announce Type: new Abstract: In joint communication & sensing (JCNS) the data signal is used to obtain parameter estimates. An example is the angle of arrival (AoA) which can be used to solve the initial access problem of beam selection. true-time delay (TTD) arrays are attractive for this purpose, as their frequency-dependent response encodes the angle information in the receive signal power spectrum. This work investigates the tradeoff between angle estimation accuracy and achievable data rate for uplink signals in a TTD array. The Fisher information (FI) for the angle is used to find the bayesian Cramer-Rao lower bound (BCRLB) under the assumption of a raised cosine distributed angle prior. Maximization of the FI under a data rate constraint is solved by waterfilling power per frequency bin dependent on sensing weights. Compared to a frequency flat signal, the optimized power allocation increases the FI \approx 4.9 dB at 5% rate loss for prior width of \pm 10{\deg}. Numerical simulations show that the derived BCRLB can be attained by a maximum likelihood (ML) estimator above an signal-to-noise ratio (SNR) threshold, confirming that the FI underlying the waveform design is attainable.
Source:https://arxiv.org/abs/2611.07911PreviousSpatial Reuse in Multi-Cell Pinching-Antenna SystemsNextPhase-Matched Design of Pinching-Antenna Elements on a 60-GHz Dielectric Rod Waveguide
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