5,480 research outputs found
The stochastic geometry of unconstrained one-bit data compression
A stationary stochastic geometric model is proposed for analyzing the data
compression method used in one-bit compressed sensing. The data set is an
unconstrained stationary set, for instance all of or a
stationary Poisson point process in . It is compressed using a
stationary and isotropic Poisson hyperplane tessellation, assumed independent
of the data. That is, each data point is compressed using one bit with respect
to each hyperplane, which is the side of the hyperplane it lies on. This model
allows one to determine how the intensity of the hyperplanes must scale with
the dimension to ensure sufficient separation of different data by the
hyperplanes as well as sufficient proximity of the data compressed together.
The results have direct implications in compressive sensing and in source
coding.Comment: 29 page
Downlink SDMA with Limited Feedback in Interference-Limited Wireless Networks
The tremendous capacity gains promised by space division multiple access
(SDMA) depend critically on the accuracy of the transmit channel state
information. In the broadcast channel, even without any network interference,
it is known that such gains collapse due to interstream interference if the
feedback is delayed or low rate. In this paper, we investigate SDMA in the
presence of interference from many other simultaneously active transmitters
distributed randomly over the network. In particular we consider zero-forcing
beamforming in a decentralized (ad hoc) network where each receiver provides
feedback to its respective transmitter. We derive closed-form expressions for
the outage probability, network throughput, transmission capacity, and average
achievable rate and go on to quantify the degradation in network performance
due to residual self-interference as a function of key system parameters. One
particular finding is that as in the classical broadcast channel, the per-user
feedback rate must increase linearly with the number of transmit antennas and
SINR (in dB) for the full multiplexing gains to be preserved with limited
feedback. We derive the throughput-maximizing number of streams, establishing
that single-stream transmission is optimal in most practically relevant
settings. In short, SDMA does not appear to be a prudent design choice for
interference-limited wireless networks.Comment: Submitted to IEEE Transactions on Wireless Communication
Statistical Multiplexing and Traffic Shaping Games for Network Slicing
Next generation wireless architectures are expected to enable slices of
shared wireless infrastructure which are customized to specific mobile
operators/services. Given infrastructure costs and the stochastic nature of
mobile services' spatial loads, it is highly desirable to achieve efficient
statistical multiplexing amongst such slices. We study a simple dynamic
resource sharing policy which allocates a 'share' of a pool of (distributed)
resources to each slice-Share Constrained Proportionally Fair (SCPF). We give a
characterization of SCPF's performance gains over static slicing and general
processor sharing. We show that higher gains are obtained when a slice's
spatial load is more 'imbalanced' than, and/or 'orthogonal' to, the aggregate
network load, and that the overall gain across slices is positive. We then
address the associated dimensioning problem. Under SCPF, traditional network
dimensioning translates to a coupled share dimensioning problem, which
characterizes the existence of a feasible share allocation given slices'
expected loads and performance requirements. We provide a solution to robust
share dimensioning for SCPF-based network slicing. Slices may wish to
unilaterally manage their users' performance via admission control which
maximizes their carried loads subject to performance requirements. We show this
can be modeled as a 'traffic shaping' game with an achievable Nash equilibrium.
Under high loads, the equilibrium is explicitly characterized, as are the gains
in the carried load under SCPF vs. static slicing. Detailed simulations of a
wireless infrastructure supporting multiple slices with heterogeneous mobile
loads show the fidelity of our models and range of validity of our high load
equilibrium analysis
A Stochastic-Geometry Approach to Coverage in Cellular Networks with Multi-Cell Cooperation
Multi-cell cooperation is a promising approach for mitigating inter-cell
interference in dense cellular networks. Quantifying the performance of
multi-cell cooperation is challenging as it integrates physical-layer
techniques and network topologies. For tractability, existing work typically
relies on the over-simplified Wyner-type models. In this paper, we propose a
new stochastic-geometry model for a cellular network with multi-cell
cooperation, which accounts for practical factors including the irregular
locations of base stations (BSs) and the resultant path-losses. In particular,
the proposed network-topology model has three key features: i) the cells are
modeled using a Poisson random tessellation generated by Poisson distributed
BSs, ii) multi-antenna BSs are clustered using a hexagonal lattice and BSs in
the same cluster mitigate mutual interference by spatial interference
avoidance, iii) BSs near cluster edges access a different sub-channel from that
by other BSs, shielding cluster-edge mobiles from strong interference. Using
this model and assuming sparse scattering, we analyze the shapes of the outage
probabilities of mobiles served by cluster-interior BSs as the average number
of BSs per cluster increases. The outage probability of a mobile near a
cluster center is shown to be proportional to where
is the fraction of BSs lying in the interior of clusters and is a
constant. Moreover, the outage probability of a typical mobile is proved to
scale proportionally with where is a constant.Comment: 5 page
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