460 research outputs found
An algorithm for optimal network planning and frequency channel assignment in indoor WLANs
The increased use of wireless local area networks has led to an increased interference and a reduced performance, as a high amount of access points are often operating on the same frequency channel. This paper presents a network planning algorithm that minimizes the number of access points required for a certain throughput and optimizes the frequency allocated to each AP, leading to reduced interference. The network planning algorithm is based on a heuristic and the frequency planning algorithm on a combination of a greedy algorithm and a Vertex-Coloring-Based Approach. The algorithm provides a good performance and has a limited computation time
WLAN Channel Selection Without Communication
In this paper we consider how a group of wireless
access-points can self-configure their channel choice so as to
avoid interference between one another and thereby maximise
network capacity. We make the observation that communication
between access points is not necessary, although it is a feature
of almost all published channel allocation algorithms. We argue
that this observation is of key practical importance as, except
in special circumstances, interfering WLANs need not all lie
in the same administrative domain and/or may be beyond
wireless communication distance (although within interference
distance). We demonstrate the feasibility of the communicationfree
paradigm via a new class of decentralized algorithms that
are simple, robust and provably correct for arbitrary interference
graphs. The algorithm requires only standard hardware and we
demonstrate its effectiveness via experimental measurements
An interference-aware virtual clustering paradigm for resource management in cognitive femtocell networks
Femtocells represent a promising alternative solution for high quality wireless access in indoor scenarios where conventional cellular system coverage can be poor. They are randomly deployed by the end user, so only post deployment network planning is possible. Furthermore, this uncoordinated deployment creates severe interference to co-located femtocells, especially in dense deployments. This paper presents a new architecture using a generalised virtual cluster femtocell (GVCF) paradigm, which groups together FAP into logical clusters. It guarantees severely interfering and overlapping femtocells are assigned to different clusters. Since each cluster operates on different band of frequencies, the corresponding virtual cluster controller only has to manage its own FAPs, so the overall system complexity is low. The performance of the GVCF algorithm is analysed from both a resource availability and cluster number perspective. Simulation results conclusively corroborate the superior performance of the GVCF model in interference mitigation, particularly in high density FAP scenarios
Enabling Parallel Wireless Communication in Mobile Robot Teams
Wireless inter-robot communication enables robot teams to cooperatively solve complex problems that cannot be addressed by a single robot. Applications for cooperative robot teams include search and rescue, exploration and surveillance. Communication is one of the most important components in future autonomous robot systems and is essential for core functions such as inter-robot coordination, neighbour discovery and cooperative control algorithms. In environments where communication infrastructure does not exist, decentralised multi-hop networks can be constructed using only the radios on-board each robot. These are known as wireless mesh networks (WMNs). However existing WMNs have limited capacity to support even small robot teams. There is a need for WMNs where links act like dedicated point-to-point connections such as in wired networks. Addressing this problem requires a fundamentally new approach to WMN construction and this thesis is the first comprehensive study in the multi-robot literature to address these challenges. In this thesis, we propose a new class of communication systems called zero mutual interference (ZMI) networks that are able to emulate the point-to-point properties of a wired network over a WMN implementation. We instantiate the ZMI network using a multi-radio multi-channel architecture that autonomously adapts its topology and channel allocations such that all network edges communicate at the full capacity of the radio hardware. We implement the ZMI network on a 100-radio testbed with up to 20-individual nodes and verify its theoretical properties. Mobile robot experiments also demonstrate these properties are practically achievable. The results are an encouraging indication that the ZMI network approach can facilitate the communication demands of large cooperative robot teams deployed in practical problems such as data pipe-lining, decentralised optimisation, decentralised data fusion and sensor networks
Random graph models for wireless communication networks
PhDThis thesis concerns mathematical models of wireless communication networks, in particular
ad-hoc networks and 802:11 WLANs. In ad-hoc mode each of these devices may
function as a sender, a relay or a receiver. Each device may only communicate with other
devices within its transmission range. We use graph models for the relationship between
any two devices: a node stands for a device, and an edge for a communication link, or
sometimes an interference relationship. The number of edges incident on a node is the
degree of this node. When considering geometric graphs, the coordinates of a node give
the geographical position of a node.
One of the important properties of a communication graph is its connectedness |
whether all nodes can reach all other nodes. We use the term connectivity, the probability
of graphs being connected given the number of nodes and the transmission range to measure
the connectedness of a wireless network. Connectedness is an important prerequisite for
all communication networks which communication between nodes. This is especially true
for wireless ad-hoc networks, where communication relies on the contact among nodes and
their neighbours.
Another important property of an interference graph is its chromatic number | the
minimum number of colours needed so that no adjacent nodes are assigned the same colour.
Here adjacent nodes share an edge; adjacent edges share at least one node; and colours
are used to identify di erent frequencies. This gives the minimum number of frequencies
a network needs in order to attain zero interference. This problem can be solved as an
optimization problem deterministically, but is algorithmically NP-hard. Hence, nding
good asymptotic approximations for this value becomes important.
Random geometric graphs describe an ensemble of graphs which share common features.
In this thesis, node positions follow a Poisson point process or a binomial point
process. We use probability theory to study the connectedness of random graphs and
random geometric graphs, which is the fraction of connected graphs among many graph
samples. This probability is closely related to the property of minimum node degree being
at least unity. The chromatic number is closely related to the maximum degree as n ! 1;
the chromatic number converges to maximum degree when graph is sparse. We test existing
theorems and improve the existing ones when possible. These motivated me to study
the degree of random (geometric) graph models.
We study using deterministic methods some degree-related problems for Erda}os-R enyi
random graphs G(n; p) and random geometric graphs G(n; r). I provide both theoretical
analysis and accurate simulation results. The results lead to a study of dependence or
non-dependence in the joint distribution of the degrees of neighbouring nodes.
We study the probability of no node being isolated in G(n; p), that is, minimum node
degree being at least unity. By making the assumption of non-dependence of node degree,
we derive two asymptotics for this probability. The probability of no node being isolated is
an approximation to the probability of the graph being connected. By making an analogy
to G(n; p), we study this problem for G(n; r), which is a more realistic model for wireless
networks. Experiment shows that this asymptotic result also works well for small graphs.
We wish to nd the relationship between these basic features the above two important
problems of wireless networks: the probability of a network being connected and the
minimum number of channels a network needs in order to minimize interference.
Inspired by the problem of maximum degree in random graphs, we study the problem
of the maximum of a set of Poisson random variables and binomial random variables,
which leads to two accurate formulae for the mode of the maximum for general random
geometric graphs and for sparse random graphs. To our knowledge, these are the best
results for sparse random geometric graphs in the literature so far. By approximating
the node degrees as independent Poisson or binomial variables, we apply the result to the
problem of maximum degree in general and sparse G(n; r), and derived much more accurate
results than in the existing literature. Combining the limit theorem from Penrose and our
work, we provide good approximations for the mode of the clique number and chromatic
number in sparse G(n; r). Again these results are much more accurate than existing ones.
This has implications for the interference minimization of WLANs.
Finally, we apply our asymptotic result based on Poisson distribution for the chromatic
number of random geometric graph to the interference minimization problem in IEEE
802:11b/g WLAN. Experiments based on the real planned position of the APs in WLANs
show that our asymptotic results estimate the minimum number of channels needed accurately.
This also means that sparse random geometric graphs are good models for interference
minimization problem of WLANs. We discuss the interference minimization
problem in single radio and multi-radio wireless networking scenarios. We study branchand-
bound algorithms for these scenarios by selecting di erent constraint functions and
objective functions
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Interference Aware Cognitive Femtocell Networks
Femtocells Access Points (FAP) are low power, plug and play home base stations which are designed to extend the cellular radio range in indoor environments where macrocell coverage is generally poor. They offer significant increases in data rates over a short range, enabling high speed wireless and mobile broadband services, with the femtocell network overlaid onto the macrocell in a dual-tier arrangement. In contrast to conventional cellular systems which are well planned, FAP are arbitrarily installed by the end users and this can create harmful interference to both collocated femtocell and macrocell users. The interference becomes particularly serious in high FAP density scenarios and compromises the ensuing data rate. Consequently, effective management of both cross and co-tier interference is a major design challenge in dual-tier networks.
Since traditional radio resource management techniques and architectures for single-tier systems are either not applicable or operate inefficiently, innovative dual-tier approaches to intelligently manage interference are required. This thesis presents a number of original contributions to fulfill this objective including, a new hybrid cross-tier spectrum sharing model which builds upon an existing fractional frequency reuse technique to ensure minimal impact on the macro-tier resource allocation. A new flexible and adaptive virtual clustering framework is then formulated to alleviate co-tier interference in high FAP densities situations and finally, an intelligent coverage extension algorithm is developed to mitigate excessive femto-macrocell handovers, while upholding the required quality of service provision.
This thesis contends that to exploit the undoubted potential of dual-tier, macro-femtocell architectures an interference awareness solution is necessary. Rigorous evidence confirms that noteworthy performance improvements can be achieved in the quality of the received signal and throughput by applying cognitive methods to manage interference
Efficient Control Message Dissemination in Dense Wireless Lighting Networks
Modern lighting systems using LED light sources lead to dense lighting installations. The control of such systems using wireless Machine-to-Machine (M2M) where standard LED light sources are replaced by wirelessly controllable LED light sources create new problems which are investigated in this thesis. Current approaches for control message transmission is such networks are based on broadcasting messages among luminaires. However, adequate communication performance - in particular, sufficiently low latency and synchronicity - is difficult to ensure in such networks, in particular, if the network is part of a wireless building management system and carries not only low-latency broadcast messages but also collects data from sensors. In this thesis, the problem of simultaneously controlling dense wireless lighting control networks with a higher number of luminaires is addressed. Extensive computer simulation shows that current state-of-the-art protocols are not suitable for lighting control applications, especially if complex applications are required such as dimming or colour tuning. The novel D³LC-Suite is proposed, which is specially designed for dense wireless lighting control networks. This suite includes three sub-protocols. First, a protocol to organize a network in form of a cluster tree named CIDER. To ensure that intra-cluster messages can be exchanged simultaneously, a weighted colouring algorithm is applied to reduce the inter cluster interference. To disseminate efficiently control messages a protocol is proposed named RLL. The D³LC-Suite is evaluated and validated using different methods. A convergence analysis show that CIDER is able to form a network in a matter of minutes. Simulation results of RLL indicate that this protocol is well suited for dense wireless applications. In extensive experiments, it is shown that the D³LC-Suite advances the current state-of-the-art in several aspects. The suite is able to deliver control messages across multiple hops meeting the requirements of lighting applications. Especially, it provides a deterministic latency, very promising packet loss ratios in low interference environments, and mechanisms for simultaneous message delivery which is important in terms of Quality of Experience (QoE
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