Prabhakar R. Chitrapu

Motion artifact cancellation in NIR spectroscopy using discrete Kalman filtering.

BackgroundAs a continuation of our earlier work, we present in this study a Kalman filtering based algorithm for the elimination of motion artifacts present in Near Infrared spectroscopy (NIR) measurements. Functional NIR measurements suffer from head motion especially in real world applications where movement cannot be restricted such as studies involving pilots, children, etc. Since head movement can cause fluctuations unrelated to metabolic changes in the blood due to the cognitive activity, removal of these artifacts from NIR signal is necessary for reliable assessment of cognitive activity in the brain for real life applications.MethodsPreviously, we had worked on adaptive and Wiener filtering for the cancellation of motion artifacts in NIR studies. Using the same NIR data set we have collected in our previous work where different speed motion artifacts were induced on the NIR measurements we compared the results of the newly proposed Kalman filtering approach with the results of previously studied adaptive and Wiener filtering methods in terms of gains in signal to noise ratio. Here, comparisons are based on paired t-tests where data from eleven subjects are used.ResultsThe preliminary results in this current study revealed that the proposed Kalman filtering method provides better estimates in terms of the gain in signal to noise ratio than the classical adaptive filtering approach without the need for additional sensor measurements and results comparable to Wiener filtering but better suitable for real-time applications.ConclusionsThis paper presented a novel approach based on Kalman filtering for motion artifact removal in NIR recordings. The proposed approach provides a suitable solution to the motion artifact removal problem in NIR studies by combining the advantages of the existing adaptive and Wiener filtering methods in one algorithm which allows efficient real time application with no requirement on additional sensor measurements.

Multi-RAT traffic offloading solutions for the bandwidth crunch problem

Spurred by the increasing demand for mobile broadband services and the growing number of devices supporting multiple radio access technologies (e.g., cellular, WiMAX, Wi-Fi, Bluetooth), much research is being done to improve the user experience while addressing issues related to network efficiency, congestion, interference, and cost to operators, service providers, manufacturers, and consumers alike. Standards bodies, industry players, and academia have been considering a wide range of inter-technology convergence solutions to address these issues. The solutions range from simple switching from one radio network to a “better” one, to maintaining individual application flows on multiple radio networks simultaneously and switching them dynamically as desired. More advanced solutions go one step further and aggregate the bandwidth across multiple simultaneous radio connections, thus increasing the data rates available for the applications. While the above solutions provide relief to the bandwidth crunch problem over the radio interface, different techniques are suitable to solve the loading and congestion problem over the ‘transport network’ of the Mobile Network Operators (MNOs). These include selective IP traffic offload techniques for the Core Network, and FemtoCell solutions for the Radio Access Network. In addition, FemtoCells also enable local routing of IP traffic, further reducing network load. In this paper, we shall present an overview of related standardization activities in IETF, IEEE and 3GPP, while addressing some some innovative technical solutions for residential and enterprise scenarios.

Relay Assisted Cooperative OSTBC Communication with SNR Imbalance and Channel Estimation Errors

In this paper, a two-hop relay assisted cooperative Orthogonal Space-Time Block Codes (OSTBC) transmission scheme is considered for the downlink communication of a cellular system, where the base station (BS) and the relay station (RS) cooperate and transmit data to the user equipment (UE) in a distributed fashion. We analyze the impact of the SNR imbalance between the BS-UE and RS-UE links, as well as the imperfect channel estimation at the UE receiver. The performance is analyzed in the presence of Rayleigh flat fading and our results show that the SNR imbalance does not impact the spatial diversity order. On the other hand, channel estimation errors have a larger impact on the system performance. Simulation results are then provided to confirm the analysis.

Discrete time processing of Linear Scale Invariant signals and systems

In this paper, we formulate a framework for discrete-time processing of Linear Scale Invariant (LSI) systems which are invariant to scale changes in time. Continuous-time LSI systems can be processed by Mellin and Modified Scale Transforms analogous to the use of the Laplace and Fourier Transforms in the continuous- time processing of LTI systems. In this work, we present the geometric sampling theorem to prevent aliasing in the scale domain. We also derive the perfect reconstruction filter in time domain, the discrete-time convolution sum, the Discrete Time Modified Scale Transform (DTMST) and the Discrete Modified Scale Transform (DMST) for geometrically sampled signals.