33,222 research outputs found
Communication Cost for Updating Linear Functions when Message Updates are Sparse: Connections to Maximally Recoverable Codes
We consider a communication problem in which an update of the source message
needs to be conveyed to one or more distant receivers that are interested in
maintaining specific linear functions of the source message. The setting is one
in which the updates are sparse in nature, and where neither the source nor the
receiver(s) is aware of the exact {\em difference vector}, but only know the
amount of sparsity that is present in the difference-vector. Under this
setting, we are interested in devising linear encoding and decoding schemes
that minimize the communication cost involved. We show that the optimal
solution to this problem is closely related to the notion of maximally
recoverable codes (MRCs), which were originally introduced in the context of
coding for storage systems. In the context of storage, MRCs guarantee optimal
erasure protection when the system is partially constrained to have local
parity relations among the storage nodes. In our problem, we show that optimal
solutions exist if and only if MRCs of certain kind (identified by the desired
linear functions) exist. We consider point-to-point and broadcast versions of
the problem, and identify connections to MRCs under both these settings. For
the point-to-point setting, we show that our linear-encoder based achievable
scheme is optimal even when non-linear encoding is permitted. The theory is
illustrated in the context of updating erasure coded storage nodes. We present
examples based on modern storage codes such as the minimum bandwidth
regenerating codes.Comment: To Appear in IEEE Transactions on Information Theor
Maximising Average Energy Efficiency for Two-User AWGN Broadcast Channel
Energy consumption has become an increasingly important aspect of
wireless communications, from both an economical and environmental point of
view. New enhancements are being placed on mobile networks to reduce the power
consumption of both mobile terminals and base stations. This paper studies the
achievable rate region of AWGN broadcast channels under Time-division,
Frequency-division and Superposition coding, and locates the optimal energyefficient
rate-pair according to a comparison metric based on the average energy
efficiency of the system. In addition to the transmit power, circuit power and
signalling power are also incorporated in the energy efficiency function, with
simulation results verifying that the Superposition coding scheme achieves the
highest energy efficiency in an ideal, but non-realistic scenario, where the signalling
power is zero. With moderate signalling power, the Frequency-division scheme is
the most energy-efficient, with Superposition coding and Time-division becoming
second and third best. Conversely, when the signalling power is high, both Timedivision
and Frequency-division schemes outperform Superposition coding. On the
other hand, the Superposition coding scheme also incorporates rate-fairness into the
system, which allows both users to transmit whilst maximising the energy efficiency
Message and time efficient multi-broadcast schemes
We consider message and time efficient broadcasting and multi-broadcasting in
wireless ad-hoc networks, where a subset of nodes, each with a unique rumor,
wish to broadcast their rumors to all destinations while minimizing the total
number of transmissions and total time until all rumors arrive to their
destination. Under centralized settings, we introduce a novel approximation
algorithm that provides almost optimal results with respect to the number of
transmissions and total time, separately. Later on, we show how to efficiently
implement this algorithm under distributed settings, where the nodes have only
local information about their surroundings. In addition, we show multiple
approximation techniques based on the network collision detection capabilities
and explain how to calibrate the algorithms' parameters to produce optimal
results for time and messages.Comment: In Proceedings FOMC 2013, arXiv:1310.459
Linear Precoding and Equalization for Network MIMO with Partial Cooperation
A cellular multiple-input multiple-output (MIMO) downlink system is studied
in which each base station (BS) transmits to some of the users, so that each
user receives its intended signal from a subset of the BSs. This scenario is
referred to as network MIMO with partial cooperation, since only a subset of
the BSs are able to coordinate their transmission towards any user. The focus
of this paper is on the optimization of linear beamforming strategies at the
BSs and at the users for network MIMO with partial cooperation. Individual
power constraints at the BSs are enforced, along with constraints on the number
of streams per user. It is first shown that the system is equivalent to a MIMO
interference channel with generalized linear constraints (MIMO-IFC-GC). The
problems of maximizing the sum-rate(SR) and minimizing the weighted sum mean
square error (WSMSE) of the data estimates are non-convex, and suboptimal
solutions with reasonable complexity need to be devised. Based on this,
suboptimal techniques that aim at maximizing the sum-rate for the MIMO-IFC-GC
are reviewed from recent literature and extended to the MIMO-IFC-GC where
necessary. Novel designs that aim at minimizing the WSMSE are then proposed.
Extensive numerical simulations are provided to compare the performance of the
considered schemes for realistic cellular systems.Comment: 13 pages, 5 figures, published in IEEE Transactions on Vehicular
Technology, June 201
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