A Survey on Channel Assignment for Multi-Radio Meshed Networks Maria Dolores Salmerón Pérez

Introduction: Wireless mesh networks Wireless Mesh Networks (WMNs): mix between two wireless networks topologies: ad-hoc networks and structural topology. Differences between ad-hoc networks and WMNs Topology changes Mobility Scenario of application Important research area Increasing the coverage area of the network Larger number of access points

Introduction: Wireless mesh networks WMNs and Ad hoc networks: Normally single radio systems Disadvantages: Lower throughput Nodes with half-duplex mode Many channel changes due to dynamic network traffic Interference from external sources Shared Spectrum Solution: Multiradio systems (most of the current WMN deployments adopt the multi-radio multi- channel architecture)

Introduction: Wireless mesh networks Based on the standards: IEEE 802.11 a (5 GHz) / IEEE 802.11 b (2.4 GHz) IEEE 802.11a/b standards provide respectively 12 and 3 non-overlapped frequency channel Ability to use multiple channels substantially increase the effective bandwidth available to wireless networks

Introduction: Wireless mesh networks In the standard IEEE 802.11b there are 12 available channels but only the channels 1, 6 and 11 have low interference and/or overlapping with each other.

Problem formulation A pair of nodes that use the same channel and within interference range may interfere with each other’s communication Figure (b) is an example of channel assignment for figure (a) that minimizes the number of interfering links for nodes A and B

Solution: channel assignment For any mesh network, there are multiple ways to assign channels to the radios Solution: Find a proper channel assignment in every node of the network CA algorithms Goals: Increased bandwidth Performance improvement

Solution: channel assignment Classification of Channel Assignment approaches for MR-MC WMNs : Centralized: central control Distributed: no central control

Solution: channel assignment Centralized algorithm: CLICA (Connected Low Interference Channel Assignment) Polinomial time greedy heuristic Traffic independent Based on the connectivity graph and on the conflict graph Every node is associated with a priority Coloring decisions are made node by node basis in the order of this priority Reducing interference

Solution: channel assignment Example of CLICA algorithm:

Solution: channel assignment Distributed algorithm: DCA (Distributed Coloring Algorithm) Clustering algorithm is applied previously to make set of nodes. Distributed Clustering Algorithm that find the cluster-head Cluster-head is the responsible of the graph coloring i.e. of the channel assignment Every cluster-head has a priority or weight and knows the priorities of its neighbours nodes Cluster-head colors its cluster only if highest priority cluster-head neighbors have colored completely their clusters

Solution: channel assignment Example of DCA algorithm: There are 3 types of messages that determine the action of every node: CA: allows any node to know its color UP: updates the color of one node INF: inform about forbidden colors

Solution: channel assignment Distributed algorithm: MIX (Minimum Interference Channel Selection) Clustering algorithm is applied previosly to make set of nodes. Highest Connectivity Cluster algorithm that find a cluster-head MIX is based on minimizing co-channel interference between clusters Access points have two interfaces: First interface: for inter-cluster communication Second interface: for intra-cluster communications using the channel selected by the cluster-head through MIX algorithm

Solution: channel assignment Example of MIX algorithm:

Conclusions DCA is an algorithm designed for devices on a single radio interface and a relatively low consumption MIX algorithm is the most appropriate algorithm for a larger size of network and the throughput is better than DCA CLICA has some limitations but compared with the distributed algorithms the performance is a bit better

Conclusions Centralized algorithms usually have in the most of the cases a better performance because they used entire network information Centralized algorithms: nearer throughput to the optimal Problem of the algorithms NP-hard problems (difficult to find an optimal solution and exponential runtime ) Heuristics approximation modes (not optimal results)

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