Network Coding Channel Virtualization Schemes for Satellite Multicast Communications

In this paper, we propose two novel schemes to solve the problem of finding a quasi-optimal number of coded packets to multicast to a set of independent wireless receivers suffering different channel conditions. In particular, we propose two network channel virtualization schemes that allow for representing the set of intended receivers in a multicast group to be virtualized as one receiver. Such approach allows for a transmission scheme not only adapted to per-receiver channel variation over time, but to the network-virtualized channel representing all receivers in the multicast group. The first scheme capitalizes on a maximum erasure criterion introduced via the creation of a virtual worst per receiver per slot reference channel of the network. The second scheme capitalizes on a maximum completion time criterion by the use of the worst performing receiver channel as a virtual reference to the network. We apply such schemes to a GEO satellite scenario. We demonstrate the benefits of the proposed schemes comparing them to a per-receiver point-to-point adaptive strategy

Optimal Energy Management for Energy Harvesting Transmitter and Receiver with Helper

We study energy harvesting (EH) transmitter and receiver, where the receiver decodes data using the harvested energy from the nature and from an independent EH node, named helper. Helper cooperates with the receiver by transferring its harvested energy to the receiver over an orthogonal fading channel. We study an offline optimal power management policy to maximize the reliable information rate. The harvested energy in all three nodes are assumed to be known. We consider four different scenarios; First, for the case that both transmitter and the receiver have batteries, we show that the optimal policy is transferring the helper harvested energy to the receiver, immediately. Next, for the case of non-battery receiver and full power transmitter, we model a virtual EH receiver with minimum energy constraint to achieve an optimal policy. Then, we consider a non-battery EH receiver and EH transmitter with battery. Finally, we derive optimal power management wherein neither the transmitter nor the receiver have batteries. We propose three iterative algorithms to compute optimal energy management policies. Numerical results are presented to corroborate the advantage of employing the helper.Comment: It is a conference paper with 5 pages and one figure, submitted to ISITA201

Monitoring induced distributed double-couple sources using Marchenko-based virtual receivers

We aim to monitor and characterize signals in the subsurface by combining these passive signals with recorded reflection data at the surface of the Earth. To achieve this, we propose a method to create virtual receivers from reflection data using the Marchenko method. By applying homogeneous Green's function retrieval, these virtual receivers are then used to monitor the responses from subsurface sources. We consider monopole point sources with a symmetric source signal, where the full wavefield without artefacts in the subsurface can be obtained. Responses from more complex source mechanisms, such as double-couple sources, can also be used and provide results with comparable quality as the monopole responses. If the source signal is not symmetric in time, our technique that is based on homogeneous Green's function retrieval provides an incomplete signal, with additional artefacts. The duration of these artefacts is limited and they are only present when the source of the signal is located above the virtual receiver. For sources along a fault rupture, this limitation is also present and more severe due to the source activating over a longer period of time. Part of the correct signal is still retrieved, as well as the source location of the signal. These artefacts do not occur in another method which creates virtual sources as well as receivers from reflection data at the surface. This second method can be used to forecast responses to possible future induced seismicity sources (monopoles, double-couple sources and fault ruptures). This method is applied to field data, where similar results to synthetic data are achieved, which shows the potential for the application on real data signals

Multiple-Input Multiple-Output Gaussian Broadcast Channels with Common and Confidential Messages

This paper considers the problem of the multiple-input multiple-output (MIMO) Gaussian broadcast channel with two receivers (receivers 1 and 2) and two messages: a common message intended for both receivers and a confidential message intended only for receiver 1 but needing to be kept asymptotically perfectly secure from receiver 2. A matrix characterization of the secrecy capacity region is established via a channel enhancement argument. The enhanced channel is constructed by first splitting receiver 1 into two virtual receivers and then enhancing only the virtual receiver that decodes the confidential message. The secrecy capacity region of the enhanced channel is characterized using an extremal entropy inequality previously established for characterizing the capacity region of a degraded compound MIMO Gaussian broadcast channel.Comment: Submitted to the IEEE Transactions on Information Theory, July 200

Distortion Minimization in Gaussian Layered Broadcast Coding with Successive Refinement

A transmitter without channel state information (CSI) wishes to send a delay-limited Gaussian source over a slowly fading channel. The source is coded in superimposed layers, with each layer successively refining the description in the previous one. The receiver decodes the layers that are supported by the channel realization and reconstructs the source up to a distortion. The expected distortion is minimized by optimally allocating the transmit power among the source layers. For two source layers, the allocation is optimal when power is first assigned to the higher layer up to a power ceiling that depends only on the channel fading distribution; all remaining power, if any, is allocated to the lower layer. For convex distortion cost functions with convex constraints, the minimization is formulated as a convex optimization problem. In the limit of a continuum of infinite layers, the minimum expected distortion is given by the solution to a set of linear differential equations in terms of the density of the fading distribution. As the bandwidth ratio b (channel uses per source symbol) tends to zero, the power distribution that minimizes expected distortion converges to the one that maximizes expected capacity. While expected distortion can be improved by acquiring CSI at the transmitter (CSIT) or by increasing diversity from the realization of independent fading paths, at high SNR the performance benefit from diversity exceeds that from CSIT, especially when b is large.Comment: Accepted for publication in IEEE Transactions on Information Theor

Virtual plane-wave imaging via Marchenko redatuming

Marchenko redatuming is a novel scheme used to retrieve up- and down-going Green's functions in an unknown medium. Marchenko equations are based on reciprocity theorems and are derived on the assumption of the existence of so called focusing functions, i.e. functions which exhibit time-space focusing properties once injected in the subsurface. In contrast to interferometry but similarly to standard migration methods, Marchenko redatuming only requires an estimate of the direct wave from the virtual source (or to the virtual receiver), illumination from only one side of the medium, and no physical sources (or receivers) inside the medium. In this contribution we consider a different time-focusing condition within the frame of Marchenko redatuming and show how this can lead to the retrieval of virtual plane-wave responses, thus allowing multiple-free imaging using only a 1 dimensional sampling of the targeted model. The potential of the new method is demonstrated on a 2D synthetic model.Comment: 12 pages, 5 figure