789 research outputs found
Proactive Resource Allocation: Harnessing the Diversity and Multicast Gains
This paper introduces the novel concept of proactive resource allocation
through which the predictability of user behavior is exploited to balance the
wireless traffic over time, and hence, significantly reduce the bandwidth
required to achieve a given blocking/outage probability. We start with a simple
model in which the smart wireless devices are assumed to predict the arrival of
new requests and submit them to the network T time slots in advance. Using
tools from large deviation theory, we quantify the resulting prediction
diversity gain} to establish that the decay rate of the outage event
probabilities increases with the prediction duration T. This model is then
generalized to incorporate the effect of the randomness in the prediction
look-ahead time T. Remarkably, we also show that, in the cognitive networking
scenario, the appropriate use of proactive resource allocation by the primary
users improves the diversity gain of the secondary network at no cost in the
primary network diversity. We also shed lights on multicasting with predictable
demands and show that the proactive multicast networks can achieve a
significantly higher diversity gain that scales super-linearly with T. Finally,
we conclude by a discussion of the new research questions posed under the
umbrella of the proposed proactive (non-causal) wireless networking framework
Coordinated Multicast Beamforming in Multicell Networks
We study physical layer multicasting in multicell networks where each base
station, equipped with multiple antennas, transmits a common message using a
single beamformer to multiple users in the same cell. We investigate two
coordinated beamforming designs: the quality-of-service (QoS) beamforming and
the max-min SINR (signal-to-interference-plus-noise ratio) beamforming. The
goal of the QoS beamforming is to minimize the total power consumption while
guaranteeing that received SINR at each user is above a predetermined
threshold. We present a necessary condition for the optimization problem to be
feasible. Then, based on the decomposition theory, we propose a novel
decentralized algorithm to implement the coordinated beamforming with limited
information sharing among different base stations. The algorithm is guaranteed
to converge and in most cases it converges to the optimal solution. The max-min
SINR (MMS) beamforming is to maximize the minimum received SINR among all users
under per-base station power constraints. We show that the MMS problem and a
weighted peak-power minimization (WPPM) problem are inverse problems. Based on
this inversion relationship, we then propose an efficient algorithm to solve
the MMS problem in an approximate manner. Simulation results demonstrate
significant advantages of the proposed multicast beamforming algorithms over
conventional multicasting schemes.Comment: 10pages, 9 figure
Fundamental Limits of Caching in Wireless D2D Networks
We consider a wireless Device-to-Device (D2D) network where communication is
restricted to be single-hop. Users make arbitrary requests from a finite
library of files and have pre-cached information on their devices, subject to a
per-node storage capacity constraint. A similar problem has already been
considered in an ``infrastructure'' setting, where all users receive a common
multicast (coded) message from a single omniscient server (e.g., a base station
having all the files in the library) through a shared bottleneck link. In this
work, we consider a D2D ``infrastructure-less'' version of the problem. We
propose a caching strategy based on deterministic assignment of subpackets of
the library files, and a coded delivery strategy where the users send linearly
coded messages to each other in order to collectively satisfy their demands. We
also consider a random caching strategy, which is more suitable to a fully
decentralized implementation. Under certain conditions, both approaches can
achieve the information theoretic outer bound within a constant multiplicative
factor. In our previous work, we showed that a caching D2D wireless network
with one-hop communication, random caching, and uncoded delivery, achieves the
same throughput scaling law of the infrastructure-based coded multicasting
scheme, in the regime of large number of users and files in the library. This
shows that the spatial reuse gain of the D2D network is order-equivalent to the
coded multicasting gain of single base station transmission. It is therefore
natural to ask whether these two gains are cumulative, i.e.,if a D2D network
with both local communication (spatial reuse) and coded multicasting can
provide an improved scaling law. Somewhat counterintuitively, we show that
these gains do not cumulate (in terms of throughput scaling law).Comment: 45 pages, 5 figures, Submitted to IEEE Transactions on Information
Theory, This is the extended version of the conference (ITW) paper
arXiv:1304.585
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