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Distributed large-scale MIMO is a promising option for coping with the projected explosion in mobile traffic. It involves multiple Access Points (APs) that are connected to a central server via wired backhaul and act as a distributed MIMO transmitter, serving multiple users via spatial precoding. As is well known, large downlink (DL) spectral efficiencies(More)
Large-scale distributed Multiuser MIMO (MU-MIMO) is a promising wireless network architecture that combines the advantages of " massive MIMO " and " small cells. " It consists of several Access Points (APs) connected to a central server via a wired backhaul network and acting as a large distributed antenna system. We focus on the downlink, which is both(More)
Massive MIMO is expected to play a key role in coping with the predicted mobile-data traffic explosion. Indeed, in combination with small cells and TDD operation, it promises large throughputs per unit area with low latency. In this paper we focus on the problem of balancing the load across networks with massive MIMO base-stations (BSs). The need for load(More)
The use of a very large number of antennas at each base station site (referred to as " Massive MIMO ") is one of the most promising approaches to cope with the predicted wireless data traffic explosion. In combination with Time Division Duplex and with simple per-cell processing, it achieves large throughput per cell, low latency, and attractive power(More)
We present a novel distributed video coding algorithm based on transform coding of distributed sources and exploiting the geometrical relationships between the location of the sensors. The geometry is used to align the video sequences and distributed quantization of transform coefficients is used to eliminate spatial and inter-sensor redundancy. In contrast(More)
The straightforward application of Shannon's separation principle may entail a significant suboptimality in practical systems with limited coding delay and complexity. This is particularly evident when the lossy source code is based on entropy-coded quantization. In fact, it is well known that entropy coding is not robust to residual channel errors. In this(More)
A new coding scheme for image transmission over noisy channel is proposed. Similar to standard image compression, the scheme includes a linear transform followed by embedded scalar quantization. Joint source-channel coding is implemented by optimizing the rate allocation across the source subbands, treated as the components of a parallel source model. The(More)
— Dense large-scale antenna deployments are one of the most promising technologies for delivering very large throughputs per unit area in the downlink (DL) of cellular networks. We consider such a dense deployment involving a distributed system formed by multi-antenna remote radio head (RRH) units connected to the same fronthaul serving a geographical area.(More)
—Multi-tier networks with large-array base stations (BSs) that are able to operate in the " massive MIMO " regime are envisioned to play a key role in meeting the exploding wireless traffic demands. Operated over small cells with reciprocity-based training, massive MIMO promises large spectral efficiencies per unit area with low overheads. Also,(More)
SUMMARY Massive MIMO is widely recognized as an essential technology for 5G. Together with newly allocated spectrum (bandwidth) and network densification (small cells), it is expected to play a key role in coping with the ongoing explosion in data-traffic demand and services. Compared to 4G MIMO technologies, massive MIMO can offer large gains in cell(More)