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Michael Christoph Gastpar

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Publications associées (132)

Functional Forwarding of Channel State Information

Michael Christoph Gastpar

Based on the recent compute-and-forward technique [1], a novel communication strategy is proposed under which functions of the channel state information are forwarded along the network. Those functions are chosen such that on the one hand, they can be effi ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Integer-forcing Linear Receivers

Michael Christoph Gastpar

Linear receivers are often used to reduce the implementation complexity of multiple-antenna systems. In a traditional linear receiver architecture, the receive antennas are used to separate out the codewords sent by each transmit antenna, which can then be ...

Institute of Electrical and Electronics Engineers2014

Compute-and-forward for discrete memoryless networks

Michael Christoph Gastpar

Consider a receiver that observes multiple interfering codewords. The compute-and-forward technique makes it possible for the receiver to directly decode linear combinations of the codewords. Previous work has focused on compute-and-forward for linear Gaus ...

2014

On the energy benefit of compute-and-forward on the hexagonal lattice

Michael Christoph Gastpar, Jasper Goseling

2014

Capacity Scaling of Cognitive Networks: Beyond Interference-Limited Communication

Michael Christoph Gastpar

The capacity scaling laws of two overlaid networks are investigated, which are located in the same area sharing the same wireless resources with different priorities. The primary network can be regarded as an existing communication system operated in a lic ...

Institute of Electrical and Electronics Engineers2014

Compute-and-Forward: Finding the Best Equation

Michael Christoph Gastpar, Saeid Sahraei

Compute-and-Forward is an emerging technique to deal with interference. It allows the receiver to decode a suitably chosen integer linear combination of the transmitted messages. The integer coefficients should be adapted to the channel fading state. Optim ...

2014

Maximum Throughput Gain of Compute-and-Forward for Multiple Unicast

Michael Christoph Gastpar, Jasper Goseling

Compute-and-Forward (CF), also known as reliable physical layer network coding, is a technique that provides the possibility of exploiting the features of broadcast and superposition in wireless networks. It has been shown that the throughput for multiple ...

Institute of Electrical and Electronics Engineers2014

On Distributed Successive Refinement with Lossless Recovery

Michael Christoph Gastpar, Chien-Yi Wang

The problem of successive refinement in distributed source coding and in joint source-channel coding is considered. The emphasis is placed on the case where the sources have to be recovered losslessly in the second stage. In distributed source coding, it i ...

2014

Gaussian (dirty) multiple access channels: a compute-and-forward perspective

Michael Christoph Gastpar, Jingge Zhu

Lattice codes are applied to the two-user Gaussian multiple access channel (MAC) combined with a modified compute-and-forward transmitting scheme. It is shown that non-corner points on the boundary of the capacity region can be achieved by decoding two int ...

IEEE2014

Computation Over Gaussian Networks With Orthogonal Components

Michael Christoph Gastpar, Chien-Yi Wang

Function computation over Gaussian networks with orthogonal components is studied for arbitrarily correlated discrete memoryless sources. Two classes of functions are considered: 1) the arithmetic sum function and 2) the type function. The arithmetic sum f ...

Institute of Electrical and Electronics Engineers2014

Successive Refinement of Gaussian Projections

Michael Christoph Gastpar, Guillaume Jean Op 't Veld

Successive refinement is a technique to encode a source iteratively, improving the distortion at each step. If the code rates of all steps combined can be as efficient as coding only for the final distortion in one go, then the source is said to be success ...

2014

Approximate Sparsity Pattern Recovery: Information-Theoretic Lower Bounds

Michael Christoph Gastpar

Recovery of the sparsity pattern (or support) of an unknown sparse vector from a small number of noisy linear mea- surements is an important problem in compressed sensing. In this paper, the high-dimensional setting is considered. It is shown that if the m ...

Institute of Electrical and Electronics Engineers2013

Multi-round computation of type-threshold functions in collocated Gaussian networks

Michael Christoph Gastpar, Chien-Yi Wang

In wireless sensor networks, various applications involve learning one or multiple functions of the measurements observed by sensors, rather than the measurements themselves. This paper focuses on the computation of type-threshold functions which include t ...

2013

Computation over Gaussian networks with orthogonal components

Michael Christoph Gastpar, Chien-Yi Wang

Function computation of arbitrarily correlated discrete sources over Gaussian networks with multiple access components but no broadcast is studied. Two classes of functions are considered: the arithmetic sum function and the frequency histogram function. T ...

2013

Capacity Scaling of Cognitive Networks: Beyond Interference-Limited Communication

Michael Christoph Gastpar

The capacity scaling laws of two overlaid networks sharing the same wireless resources with different priorities are investigated. The primary network is assumed to operate in an order-optimal fashion to achieve its standalone capacity scaling law. The sec ...

2013

Polar Codes For Broadcast Channels

Emmanuel Abbé, Michael Christoph Gastpar, Naveen Goela

Building on polar code constructions proposed by the authors for deterministic broadcast channels, two theorems are introduced in the present paper for noisy two-user broadcast channels. The theorems establish polar code constructions for two important ...

2013

Function Identification in Neuron Populations via Information Bottleneck

Michael Christoph Gastpar, Sreenivas Kartik Buddha

It is plausible to hypothesize that the spiking responses of certain neurons represent functions of the spiking signals of other neurons. A natural ensuing question concerns how to use experimental data to infer what kind of a function is being computed. M ...

MDPI AG2013

Physical-layer Network Coding on the Random-access Channel

Michael Christoph Gastpar, Jasper Goseling

We consider a physical-layer network coding strat- egy for the random-access channel, based on compute-and- forward. When packets collide, it is possible to reliably recover a linear combination of the packets at the receiver. Over many rounds of transmiss ...

2013

Real-time Prediction of Fast and Slow Delivery of Mental Commands in a Motor Imagery BCI: An Entropy-based Approach

Michael Christoph Gastpar, Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Sareh Saeedi

Providing adaptive shared control for Brain- Computer Interfaces (BCIs) can result in better performance while reducing the user’s mental workload. In this respect, online estimation of accuracy and speed of command delivery are important factors. This stu ...

2012

Approximate Ergodic Capacity of a Class of Fading 2-user 2-hop Networks

Michael Christoph Gastpar, Chien-Yi Wang

We consider a fading AWGN 2-user 2-hop network in which the channel coefficients are independently and identically distributed (i.i.d.) drawn from a continuous distribution and vary over time. For a broad class of channel distributions, we characterize the ...

Ieee2012

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