24 research outputs found
Coverage probability in wireless networks with determinantal scheduling
We propose a new class of algorithms for randomly scheduling network
transmissions. The idea is to use (discrete) determinantal point processes
(subsets) to randomly assign medium access to various {\em repulsive} subsets
of potential transmitters. This approach can be seen as a natural extension of
(spatial) Aloha, which schedules transmissions independently. Under a general
path loss model and Rayleigh fading, we show that, similarly to Aloha, they are
also subject to elegant analysis of the coverage probabilities and transmission
attempts (also known as local delay). This is mainly due to the explicit,
determinantal form of the conditional (Palm) distribution and closed-form
expressions for the Laplace functional of determinantal processes.
Interestingly, the derived performance characteristics of the network are
amenable to various optimizations of the scheduling parameters, which are
determinantal kernels, allowing the use of techniques developed for statistical
learning with determinantal processes. Well-established sampling algorithms for
determinantal processes can be used to cope with implementation issues, which
is is beyond the scope of this paper, but it creates paths for further
research.Comment: 8 pages. 2 figure
Exploiting Regional Differences: A Spatially Adaptive Random Access
In this paper, we discuss the potential for improvement of the simple random
access scheme by utilizing local information such as the received
signal-to-interference-plus-noise-ratio (SINR). We propose a spatially adaptive
random access (SARA) scheme in which the transmitters in the network utilize
different transmit probabilities depending on the local situation. In our
proposed scheme, the transmit probability is adaptively updated by the ratio of
the received SINR and the target SINR. We investigate the performance of the
spatially adaptive random access scheme. For the comparison, we derive an
optimal transmit probability of ALOHA random access scheme in which all
transmitters use the same transmit probability. We illustrate the performance
of the spatially adaptive random access scheme through simulations. We show
that the performance of the proposed scheme surpasses that of the optimal ALOHA
random access scheme and is comparable with the CSMA/CA scheme.Comment: 10 pages, 10 figure
An Upper Bound on Multi-hop Transmission Capacity with Dynamic Routing Selection
This paper develops upper bounds on the end-to-end transmission capacity of
multi-hop wireless networks. Potential source-destination paths are dynamically
selected from a pool of randomly located relays, from which a closed-form lower
bound on the outage probability is derived in terms of the expected number of
potential paths. This is in turn used to provide an upper bound on the number
of successful transmissions that can occur per unit area, which is known as the
transmission capacity. The upper bound results from assuming independence among
the potential paths, and can be viewed as the maximum diversity case. A useful
aspect of the upper bound is its simple form for an arbitrary-sized network,
which allows insights into how the number of hops and other network parameters
affect spatial throughput in the non-asymptotic regime. The outage probability
analysis is then extended to account for retransmissions with a maximum number
of allowed attempts. In contrast to prevailing wisdom, we show that
predetermined routing (such as nearest-neighbor) is suboptimal, since more hops
are not useful once the network is interference-limited. Our results also make
clear that randomness in the location of relay sets and dynamically varying
channel states is helpful in obtaining higher aggregate throughput, and that
dynamic route selection should be used to exploit path diversity.Comment: 14 pages, 5 figures, accepted to IEEE Transactions on Information
Theory, 201
Heterogeneous Visible Light and Radio Communication for Improving Safety Message Dissemination at Road Intersection
Visible light communication (VLC) has recently emerged as an affordable and scalable technology supporting very high data rates for short range vehicle-to-vehicle (V2V) communication. In this work, we advocate the use of vehicular-VLC (V-VLC) for basic safety messages (BSMs) dissemination in lieu of conventional vehicular radio frequency (V-RF) communication in road intersection applications, where the reception performance is affected by interference from the concurrent transmissions of other vehicles. We make use of stochastic geometry to characterize the interference from the same lane as well as the perpendicular lane for various network configurations, i.e., standalone V-VLC, stand-alone V-RF and hybrid V-VLC/V-RF network. Specifically, by modelling the interfering vehicles’ locations as a spatial Poisson point process (PPP), we are able to capture a static two-dimensional road geometry as well as the impact of interference due to vehicles clustering in the vicinity of road intersection in terms of outage probability and throughput. In addition to above, the performance of spatial ALOHA and carrier sense multiple access with collision avoidance medium access control (CSMA/CA MAC) protocol for standalone V-VLC, standalone V-RF and hybrid V-VLC/V-RF network configuration for relaying BSMs at road intersection is also compared. The performance metrics such as delay outage rate (DOR) and information outage rate (IOR) are utilized to investigate the impact of latency associated with various network configurations. Our numerical results reveal that our proposed hybrid V-VLC/V-RF leads to significant improvement in terms of outage performance, throughput and latency as compared to stand-alone V-VLC or stand-alone V-RF network
Characterizing the Energy Trade-Offs of End-to-End Vehicular Communications using an Hyperfractal Urban Modelling
We characterize trade-offs between the end-to-end communication delay and the
energy in urban vehicular communications with infrastructure assistance. Our
study exploits the self-similarity of the location of communication entities in
cities by modeling them with an innovative model called "hyperfractal". We show
that the hyperfractal model can be extended to incorporate road-side
infrastructure and provide stochastic geometry tools to allow a rigorous
analysis. We compute theoretical bounds for the end-to-end communication hop
count considering two different energy-minimizing goals: either total
accumulated energy or maximum energy per node. We prove that the hop count for
an end-to-end transmission is bounded by where
is the fractal dimension of the mobile nodes process.
This proves that for both constraints the energy decreases as we allow choosing
routing paths of higher length. The asymptotic limit of the energy becomes
significantly small when the number of nodes becomes asymptotically large. A
lower bound on the network throughput capacity with constraints on path energy
is also given. We show that our model fits real deployments where open data
sets are available. The results are confirmed through simulations using
different fractal dimensions in a Matlab simulator