Training-Based Antenna Selection for PER Minimization: A POMDP Approach

This paper considers the problem of receive antenna selection (AS) in a multiple-antenna communication system having a single radio-frequency (RF) chain. The AS decisions are based on noisy channel estimates obtained using known pilot symbols embedded in the data packets. The goal here is to minimize the average packet error rate (PER) by exploiting the known temporal correlation of the channel. As the underlying channels are only partially observed using the pilot symbols, the problem of AS for PER minimization is cast into a partially observable Markov decision process (POMDP) framework. Under mild assumptions, the optimality of a myopic policy is established for the two-state channel case. Moreover, two heuristic AS schemes are proposed based on a weighted combination of the estimated channel states on the different antennas. These schemes utilize the continuous valued received pilot symbols to make the AS decisions, and are shown to offer performance comparable to the POMDP approach, which requires one to quantize the channel and observations to a finite set of states. The performance improvement offered by the POMDP solution and the proposed heuristic solutions relative to existing AS training-based approaches is illustrated using Monte Carlo simulations.

Interlaboratory comparison of magnesium isotopic compositions of 12 felsic to ultramafic igneous rock standards analyzed by MC-ICPMS

To evaluate the interlaboratory mass bias for high-precision stable Mg isotopic analysis of natural materials, a suite of silicate standards ranging in composition from felsic to ultramafic were analyzed in five laboratories by using three types of multicollector inductively coupled plasma mass spectrometer (MC-ICPMS). Magnesium isotopic compositions from all labs are in agreement for most rocks within quoted uncertainties but are significantly (up to 0.3 parts per thousand in Mg-26/Mg-24, > 4 times of uncertainties) different for some mafic samples. The interlaboratory mass bias does not correlate with matrix element/Mg ratios, and the mechanism for producing it is uncertain but very likely arises from column chemistry. Our results suggest that standards with different matrices are needed to calibrate the efficiency of column chemistry and caution should be taken when dealing with samples with complicated matrices. Well-calibrated standards with matrix elements matching samples should be used to reduce the interlaboratory mass bias.