7,054 research outputs found
Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions
Massive MIMO is a compelling wireless access concept that relies on the use
of an excess number of base-station antennas, relative to the number of active
terminals. This technology is a main component of 5G New Radio (NR) and
addresses all important requirements of future wireless standards: a great
capacity increase, the support of many simultaneous users, and improvement in
energy efficiency. Massive MIMO requires the simultaneous processing of signals
from many antenna chains, and computational operations on large matrices. The
complexity of the digital processing has been viewed as a fundamental obstacle
to the feasibility of Massive MIMO in the past. Recent advances on
system-algorithm-hardware co-design have led to extremely energy-efficient
implementations. These exploit opportunities in deeply-scaled silicon
technologies and perform partly distributed processing to cope with the
bottlenecks encountered in the interconnection of many signals. For example,
prototype ASIC implementations have demonstrated zero-forcing precoding in real
time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing
of 8 terminals). Coarse and even error-prone digital processing in the antenna
paths permits a reduction of consumption with a factor of 2 to 5. This article
summarizes the fundamental technical contributions to efficient digital signal
processing for Massive MIMO. The opportunities and constraints on operating on
low-complexity RF and analog hardware chains are clarified. It illustrates how
terminals can benefit from improved energy efficiency. The status of technology
and real-life prototypes discussed. Open challenges and directions for future
research are suggested.Comment: submitted to IEEE transactions on signal processin
Fundamentals of Large Sensor Networks: Connectivity, Capacity, Clocks and Computation
Sensor networks potentially feature large numbers of nodes that can sense
their environment over time, communicate with each other over a wireless
network, and process information. They differ from data networks in that the
network as a whole may be designed for a specific application. We study the
theoretical foundations of such large scale sensor networks, addressing four
fundamental issues- connectivity, capacity, clocks and function computation.
To begin with, a sensor network must be connected so that information can
indeed be exchanged between nodes. The connectivity graph of an ad-hoc network
is modeled as a random graph and the critical range for asymptotic connectivity
is determined, as well as the critical number of neighbors that a node needs to
connect to. Next, given connectivity, we address the issue of how much data can
be transported over the sensor network. We present fundamental bounds on
capacity under several models, as well as architectural implications for how
wireless communication should be organized.
Temporal information is important both for the applications of sensor
networks as well as their operation.We present fundamental bounds on the
synchronizability of clocks in networks, and also present and analyze
algorithms for clock synchronization. Finally we turn to the issue of gathering
relevant information, that sensor networks are designed to do. One needs to
study optimal strategies for in-network aggregation of data, in order to
reliably compute a composite function of sensor measurements, as well as the
complexity of doing so. We address the issue of how such computation can be
performed efficiently in a sensor network and the algorithms for doing so, for
some classes of functions.Comment: 10 pages, 3 figures, Submitted to the Proceedings of the IEE
On Two-Pair Two-Way Relay Channel with an Intermittently Available Relay
When multiple users share the same resource for physical layer cooperation
such as relay terminals in their vicinities, this shared resource may not be
always available for every user, and it is critical for transmitting terminals
to know whether other users have access to that common resource in order to
better utilize it. Failing to learn this critical piece of information may
cause severe issues in the design of such cooperative systems. In this paper,
we address this problem by investigating a two-pair two-way relay channel with
an intermittently available relay. In the model, each pair of users need to
exchange their messages within their own pair via the shared relay. The shared
relay, however, is only intermittently available for the users to access. The
accessing activities of different pairs of users are governed by independent
Bernoulli random processes. Our main contribution is the characterization of
the capacity region to within a bounded gap in a symmetric setting, for both
delayed and instantaneous state information at transmitters. An interesting
observation is that the bottleneck for information flow is the quality of state
information (delayed or instantaneous) available at the relay, not those at the
end users. To the best of our knowledge, our work is the first result regarding
how the shared intermittent relay should cooperate with multiple pairs of users
in such a two-way cooperative network.Comment: extended version of ISIT 2015 pape
The Three-Terminal Interactive Lossy Source Coding Problem
The three-node multiterminal lossy source coding problem is investigated. We
derive an inner bound to the general rate-distortion region of this problem
which is a natural extension of the seminal work by Kaspi'85 on the interactive
two-terminal source coding problem. It is shown that this (rather involved)
inner bound contains several rate-distortion regions of some relevant source
coding settings. In this way, besides the non-trivial extension of the
interactive two terminal problem, our results can be seen as a generalization
and hence unification of several previous works in the field. Specializing to
particular cases we obtain novel rate-distortion regions for several lossy
source coding problems. We finish by describing some of the open problems and
challenges. However, the general three-node multiterminal lossy source coding
problem seems to offer a formidable mathematical complexity.Comment: New version with changes suggested by reviewers.Revised and
resubmitted to IEEE Transactions on Information Theory. 92 pages, 11 figures,
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