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In this paper we consider the classical problem of blind deconvolution of multiple signals from its superposition, also called blind demixing and deconvolution. One is given a signal ∑ri=1 wi ∗ xi = y ∊ RL which is the superposition of r unknown source signals {xi}ri=1 and convolution kernels {wi}ri=1 The goal is to reconstruct the vectors w; and x;, which are elements of known but random subspaces...
We consider a device-to-device scenario in a fragmented spectrum band. Multiple devices transmit complex symbols with a single antenna on distributed, but disjoint OFDM resources. The devices select sufficient frequency resources to enable channel estimation, if the receiver has complete knowledge of the resource map. However, in this scenario the actual allocation map is unknown to the receiver....
In this paper, we utilize the framework of compressed sensing (CS) for device detection and distributed resource allocation in large-scale machine-to-machine (M2M) communication networks. The devices are partitioned into clusters according to some pre-defined criteria, e.g., proximity or service type. Moreover, by the sparse nature of the event occurrence in M2M communications, the activation pattern...
As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges, and what are the key drivers is part of intensive, ongoing discussions. Partly due to the advent of compressive sensing, methods that can optimally exploit sparsity in signals have received tremendous...
We introduce a random access procedure where control and data information is transmitted in the same “access” slot. The key idea is data-overlayed control signalling together with a dedicated frequency area for compressive measurements exploiting sparse channel profiles and, potentially, sparse user activity. This architecture is resource-efficent since otherwise pilots have to be suitably placed...
This paper proposes a novel feedback protocol for relay-based two-hop networks, in which the channel state information matrix of the second hop is compressible due to the presence of spatial correlation and distance dependent path loss among the communication channels from the relay nodes to the users. The proposed protocol makes use of recent developments in the fields of low rank matrix recovery...
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