Fading observation alignment via feedback
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Active wireless sensing: a versatile framework for information retrieval in sensor networks
IEEE Transactions on Signal Processing
PAC vs. MAC for decentralized detection using noncoherent modulation
IEEE Transactions on Signal Processing
Outage scaling laws and diversity for distributed estimation over parallel fading channels
IEEE Transactions on Signal Processing
Distributed detection in UWB wireless sensor networks
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Optimal transmitters for hypothesis testing over a Rayleigh fading MAC
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Estimation over fading channels with limited feedback using distributed sensing
IEEE Transactions on Signal Processing
Optimal relay function in the low-power regime for distributed estimation over a MAC
IEEE Transactions on Signal Processing
Distributed node selection for sequential estimation over noisy communication channels
IEEE Transactions on Wireless Communications
Distributed estimation over fading MACs with multiple antennas at the fusion center
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Universal distributed estimation over multiple access channels with constant modulus signaling
IEEE Transactions on Signal Processing
Refining decisions after losing data: the unlucky broker problem
IEEE Transactions on Signal Processing
| Hi-index | 35.71 |
We study the problem of communicating sensor readings over a Gaussian multiaccess channel. We focus on the scenario that each sensor observes a single random variable and transmits it using certain signaling in a shared channel. The objective is the design of channel waveforms (i.e., the signal constellation) to facilitate the estimation of field parameters from the channel output. We propose a communication scheme in which sensors transmit according to the type of their observations-type-based multiple access (TBMA)-and show that the TBMA is asymptotically optimal in the limit of large number of sensors if the sensor channel-gains are identical. In particular, we show that TBMA together with a variant of the maximum-likelihood estimator achieves the Cramer-Rao bound asymptotically. We then extend the asymptotic analysis of TBMA to fading channels and compare the performance of TBMA with other orthogonal allocation methods such as time-division multiple access.