Energy Efficient Coordinated Beamforming for Multi-cell MISO Systems

In this paper, we investigate the optimal energy efficient coordinated beamforming in multi-cell multiple-input single-output (MISO) systems with $K$ multiple-antenna base stations (BS) and $K$ single-antenna mobile stations (MS), where each BS sends information to its own intended MS with cooperatively designed transmit beamforming. We assume single user detection at the MS by treating the interference as noise. By taking into account a realistic power model at the BS, we characterize the Pareto boundary of the achievable energy efficiency (EE) region of the $K$ links, where the EE of each link is defined as the achievable data rate at the MS divided by the total power consumption at the BS. Since the EE of each link is non-cancave (which is a non-concave function over an affine function), characterizing this boundary is difficult. To meet this challenge, we relate this multi-cell MISO system to cognitive radio (CR) MISO channels by applying the concept of interference temperature (IT), and accordingly transform the EE boundary characterization problem into a set of fractional concave programming problems. Then, we apply the fractional concave programming technique to solve these fractional concave problems, and correspondingly give a parametrization for the EE boundary in terms of IT levels. Based on this characterization, we further present a decentralized algorithm to implement the multi-cell coordinated beamforming, which is shown by simulations to achieve the EE Pareto boundary.Comment: 6 pages, 2 figures, to be presented in IEEE GLOBECOM 201

An Energy Efficient Semi-static Power Control and Link Adaptation Scheme in UMTS HSDPA

High speed downlink packet access (HSDPA) has been successfully applied in commercial systems and improves user experience significantly. However, it incurs substantial energy consumption. In this paper, we address this issue by proposing a novel energy efficient semi-static power control and link adaptation scheme in HSDPA. Through estimating the EE under different modulation and coding schemes (MCSs) and corresponding transmit power, the proposed scheme can determine the most energy efficient MCS level and transmit power at the Node B. And then the Node B configure the optimal MCS level and transmit power. In order to decrease the signaling overhead caused by the configuration, a dual trigger mechanism is employed. After that, we extend the proposed scheme to the multiple input multiple output (MIMO) scenarios. Simulation results confirm the significant EE improvement of our proposed scheme. Finally, we give a discussion on the potential EE gain and challenge of the energy efficient mode switching between single input multiple output (SIMO) and MIMO configuration in HSDPA.Comment: 9 pages, 11 figures, accepted in EURASIP Journal on Wireless Communications and Networking, special issue on Green Radi

Patterns of Genetic Variation in Festuca hallii (Vasey) Piper across the Canadian Prairie

Festuca hallii [(Vasey) Piper] (plains rough fescue) is a dominant native grass species in the Fescue Prairie region of North America that has undergone dramatic range reduction in the past century. This research is undertaken to address the related issues associated with the effectiveness of sampling in capturing genetic diversity, the influence of habitat fragmentation on genetic variation, the geographic variation of seed germination characteristics, and the comparative genetic variation of differential germination. It was found that the tiller samples revealed slightly larger among-population variation than the seed samples. The fescue plant was genetically diverse, as revealed by the proportion of polymorphic bands, the mean band frequency, and the within-population variation. The genetic variation was not highly differentiated with only 6.5% of the total AFLP variation residing among populations. Mantel test revealed a significant correlation between genetic and geographic distances and a spatial autocorrelation up to 60 km among populations was detected. Base temperatures (Tb, minimal or base temperature permitting germination) of the 15 populations fell into a narrow range within 2.2°C with an average of 1.1°C. High final germination percentage was reached at a wide temperature range from 5 to 20°C with the highest germination percentage at 10°C. Germination rate index increased with increasing temperature from 5 to 20°C. Tb was positively correlated with latitude and negatively with longitude and the thermal time requirement for 50% germination was negatively correlated with latitude. The AFLP variation and germination responses were significantly associated with environmental attributes related to moisture, indicating local adaptation. However, the AFLP variation and germination was not significantly associated with the estimated population size and geographic distance to the nearest neighbor, suggesting that fragmentation has not generated considerable genetic and germination impact on the fescue populations. Marked differences in estimates of mean band frequency were observed for various groups of germinating seeds under different test temperatures. Comparisons of AFLP variation among 27 groups of seeds representing population, germination timing and test temperature indicates seed genotypes respond slightly differently to environmental variation, resulting in significant but small impact of germination timing and temperature on the genetic diversity of populations. These findings are significant not only for understanding and predicting the ecological adaptation of the species, but also for formulating effective restoration strategies for remnant populations

Capacity of UAV-Enabled Multicast Channel: Joint Trajectory Design and Power Allocation

This paper studies an unmanned aerial vehicle (UAV)-enabled multicast channel, in which a UAV serves as a mobile transmitter to deliver common information to a set of $K$ ground users. We aim to characterize the capacity of this channel over a finite UAV communication period, subject to its maximum speed constraint and an average transmit power constraint. To achieve the capacity, the UAV should use a sufficiently long code that spans over its whole communication period. Accordingly, the multicast channel capacity is achieved via maximizing the minimum achievable time-averaged rates of the $K$ users, by jointly optimizing the UAV's trajectory and transmit power allocation over time. However, this problem is non-convex and difficult to be solved optimally. To tackle this problem, we first consider a relaxed problem by ignoring the maximum UAV speed constraint, and obtain its globally optimal solution via the Lagrange dual method. The optimal solution reveals that the UAV should hover above a finite number of ground locations, with the optimal hovering duration and transmit power at each location. Next, based on such a multi-location-hovering solution, we present a successive hover-and-fly trajectory design and obtain the corresponding optimal transmit power allocation for the case with the maximum UAV speed constraint. Numerical results show that our proposed joint UAV trajectory and transmit power optimization significantly improves the achievable rate of the UAV-enabled multicast channel, and also greatly outperforms the conventional multicast channel with a fixed-location transmitter.Comment: To appear in the IEEE International Conference on Communications (ICC), 201