How much multiuser diversity is required over large-scale fading?

In multiuser diversity systems, the impact of large-scale fading on the total system performance such as link quality and system power has not been widely addressed. Considering large-scale fading, we propose an adaptive multiuser scheduling to minimize the total system power while reducing the effect of large-scale fading on the system bit error rate. The number of active users is adapted to every shadow variation, which varies slower than small-scale fading. We consider the two widely used multiuser systems (i.e., delay-tolerant, and delay-sensitive multiuser systems). Closed-form expressions for the bit error rate are derived. The selection procedure for the minimum number of users is introduced for guaranteed performance of the above multiuser systems. The impact of adaptive multiuser diversity gain on the system power and bit error rate is illustrated over large-scale fading channels by numerical results.

A quality-scalable and energy-efficient approach for spectral analysis of heart rate variability

Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case. 

Dual-Diversity Combining for Constrained Resource Allocation and Throughput Maximization in OFDMA Networks

Al Rawi, Anas F., Emiliano Garcia-Palacios, Sonia Aissa, Charalampos C. Tsimenidis, and Bayan S. Sharif. "Dual-Diversity Combining for Constrained Resource Allocation and Throughput Maximization in OFDMA Networks." In Vehicular Technology Conference (VTC Spring), 2013 IEEE 77th, pp. 1-5. IEEE, 2013.