Optimal training sequence design for MIMO-OFDM in spatially correlated fading

Channel estimation and training sequence design for spatially correlated fading in Multiple Input Multiple Output with Orthogonal Frequency Division Multiplexing (MIMOOFDM) systems are still open research topics of great interest. In this paper, we investigate the Linear Minimum Mean Square Error (LMMSE) channel estimation for MIMO-OFDM systems in spatially correlated fading channels. We find the lower bound of the Mean Square Error (MSE) of channel estimation. We also propose a class of training sequences which almost achieve the performance of optimal training sequences. The effectiveness of the proposed training sequences is demonstrated empirically by simulation results. © 2008 IEEE

Animal models of obesity and diabetes mellitus.

More than one-third of the worldwide population is overweight or obese and therefore at risk of developing type 2 diabetes mellitus. In order to mitigate this pandemic, safer and more potent therapeutics are urgently required. This necessitates the continued use of animal models to discover, validate and optimize novel therapeutics for their safe use in humans. In order to improve the transition from bench to bedside, researchers must not only carefully select the appropriate model but also draw the right conclusions. In this Review, we consolidate the key information on the currently available animal models of obesity and diabetes and highlight the advantages, limitations and important caveats of each of these models