We consider a windowed decoding scheme for LDPC convolutional codes that is based on the belief-propagation (BP) algorithm. We discuss the advantages of this decoding scheme and identify certain characteristics of LDPC convolutional code ensembles that exhibit good performance with the windowed decoder. We will consider the performance of these ensembles and codes over erasure channels with and without memory. We show that the structure of LDPC convolutional code ensembles is suitable to obtain performance close to the theoretical limits over the memoryless erasure channel, both for the BP decoder and windowed decoding. However, the same structure imposes limitations on the performance over erasure channels with memory.

Multibeam satellite networks in Ka band have been designed to accommodate the increasing traffic demands of the coming years. However, these systems are spectrum limited due to the current spectrum allocation policies. This paper investigates the potentials of applying cognitive radio techniques in satellite communications in order to increase the spectrum opportunities for future generation of satellite networks without interfering operation of incumbent services. These extra spectrum opportunities can potentially amount to 2.4 GHz of bandwidth in downlink, and to 2 GHz of bandwidth in uplink for high density fixed satellite services (HDFSS).

SUMMARYMulti-user multiple-input multiple-output (MU-MIMO) has allowed recent releases of terrestrial long-term evolution (LTE) standards to achieve significant improvements in terms of offered system capacity. The publication of the DVB-S2X standard and particularly of its novel superframe structure is a key enabler for applying similar interference management techniques -such as precoding-to multibeam high throughput satellite (HTS) systems. This paper presents results from the European Space Agency-funded R&D activities concerning the practical issues that arise when precoding is applied over an aggressive frequency re-use HTS network. In addressing these issues, the paper also proposes pragmatic solutions that have been developed in order to overcome these limitations. Through the application of a comprehensive system simulator, it is demonstrated that important capacity gains (beyond 40%) are to be expected from applying precoding even after introducing a number of significant practical impairments.

Abstract-In this paper, OFDM data-aided channel estimation based on the decimation of the Channel Impulse Response (CIR) through the selection of the Most Significant Samples (MSS) is addressed. Our aim is to approach the Minimum Mean Square Error (MMSE) channel estimation performance, while avoiding the need for a-priori knowledge of channel statistics (KCS). The optimal set of samples is defined in the instantaneous and average senses. We derive lower bounds on the estimation mean-square error (MSE) performance for any MSS selection strategy. We show how MSS-based channel estimation can approach these MSE lower bounds. We introduce novel MSS strategies oriented towards instantaneous decimation (Instantaneous Energy Selection -IES), and windowed decimation (Average Energy Selection -AES). We also consider decimation via Threshold Crossing Selection (TCS), which we characterize analytically, to derive the optimum threshold in the minimum MSE sense. We also propose a sub-optimal method for threshold setting that does not require KCS. Finally, we provide numerical results in terms of both MSE estimation performance and Bit Error Rate (BER) of a coded OFDM system using the proposed channel estimators, to show that they indeed approach MMSE performance.Index Terms-OFDM, channel estimation, minimum mean square error (MMSE), impulse response, pilot tone, DVB, threshold selection.

The standardization of 5G systems is entering in its critical phase, with 3GPP that will publish the PHY standard by June 2017. In order to meet the demanding 5G requirements both in terms of large throughput and global connectivity, Satellite Communications provide a valuable resource to extend and complement terrestrial networks. In this context, we consider a heterogeneous architecture in which a LEO mega-constellation satellite system provides backhaul connectivity to terrestrial 5G Relay Nodes, which create an on-ground 5G network. Since large delays and Doppler shifts related to satellite channels pose severe challenges to terrestrial-based systems, in this paper we assess their impact on the future 5G PHY and MAC layer procedures. In addition, solutions are proposed for Random Access, waveform numerology, and HARQ procedures.