We propose a novel linear minimum-mean-squared-error (MMSE) precoder design for a downlink (DL) massive multiple-input-multiple-output (MIMO) scenario. For economical and computational efficiency reasons low resolution 1-bit digital-to-analog (DAC) and analog-to-digital (ADC) converters are used. This comes at the cost of performance gain that can be recovered by the large number of antennas deployed at the base station (BS) and an appropiate precoder design to mitigate the distortions due to the coarse quantization. The proposed precoder takes the quantization non-linearities into account and is split into a digital precoder and an analog precoder. We formulate the two-stage precoding problem such that the MSE of the users is minimized under the 1-bit constraint. In the simulations, we compare the new optimized precoding scheme with previously proposed linear precoders in terms of uncoded bit error ratio (BER).Comment: Presented in ICASSP 2016, 20-25 March 2016, Shanghai, Chin

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The future of satellites lies in the deployment of high throughput satellites (HTS). Moreover, HTS will also play an important role in the up coming 5G mobile networks where HTS will provide services like disaster relief, remote automation, maritime services etc. However, the distortions caused by the on-board transponder filters and high power amplifiers (HPAs) reduce the overall performance of HTS. To increase the power and bandwidth efficiency, the transponder HPAs are often operated close to saturation and in multicarrier mode. In addition, the transponder filters are built with tighter guard bands to minimize the out-of-band (OOB) radiations. Such operation conditions introduce severe linear and nonlinear distortions in the transponder's output in terms of inter-modulation (IMD) noise, spectral regrowth, and memory effects. Digital predistortion (DPD) can effectively mitigate these distortions. This paper proposes an on-board implementation of a ground-based state-of-the-art bandlimited memory polynomial (MP) DPD method to mitigate the aforementioned distortions. The authors stress on the fact that the on-board application of the proposed ground-based DPD makes it the most suitable DPD method for HTS. However, the focus of this paper lies in the identification of the system parameters which effect the predistortion performance. To this end, the performance of the considered state-of-the-art DPD is thoroughly analyzed for varying uplink-signal, transponder and DPD specific parameters.INDEX TERMS Bandlimited predistortion, digital predistortion (DPD), high power amplifiers (HPAs), high throughput satellites (HTS), non-linear distortions, on-board processors (OBPs), parameter identification.

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Distributed clustering based techniques have been increasingly employed for outlier detection in Wireless Sensor Networks (WSNs). But despite its numerous advantages such as online and efficient computations and incorporation of spatiotemporal & attribute correlations, clustering has not been studied for event detection & identification, which is essential for smooth and reliable operations of large scale WSNs. This paper introduces the significance of clustering based event detection & identification to the research community. Further, it presents an online technique for joint event detection and identification that achieves a very high performance for synthetic and real data sets with a significant reduction in computational complexity as compared to the state-of-the-art techniques. A remarkable advantage of the proposed technique is that it can identify the key attributes in the ascending order of their contribution towards an event without incurring any additional complexity.