Dynamic channel selection algorithms for interference management in WIFI networks
A method of dynamically adjusting Wi-Fi parameters of a plurality of access points (APs) is disclosed. Reports from the plurality of APs are received through an interface. A conflict graph is created by a processor. Creating the conflict graph includes creating a plurality of vertices of the conflict graph, each vertex corresponding to one of the plurality of APs. Creating the conflict graph further includes determining that there is a conflict between at least some of the pairs of APs based at least in part on the received reports. Creating the conflict graph includes connecting an edge between each of the at least some of the pairs of APs. The conflict graph is stored in a memory.
1. A method of dynamically adjusting Wi-Fi parameters of a plurality of access points (APs), comprising:
receiving reports from the plurality of APs through an interface;
creating a conflict graph by a processor, comprising:
creating a plurality of vertices of the conflict graph, each vertex corresponding to one of the plurality of APs;
determining that there is a conflict between at least some of the pairs of APs based at least in part on the received reports;
connecting an edge between each of the at least some of the pairs of APs;
assigning a weight to each of the edges of the conflict graph; and
storing the conflict graph in a memory; and
searching for adjustments to a plurality of Wi-Fi parameters that minimize a function of the weighted edges of the conflict graph using an optimization technique, wherein the search is subject to a maximum weighted degree constraint, wherein the maximum weighted degree constraint limits the weighted degree of each AP to a predetermined threshold, wherein the maximum weighted degree constraint is determined based at least in part on a greedy heuristic, wherein the determination of the maximum weighted degree constraint comprises:
initializing the maximum weighted degree constraint to a value within a lower bound and an upper bound; and
iteratively searching for adjustments to the plurality of Wi-Fi parameters that approximately minimize the function of the weighted edges of the conflict graph using the greedy heuristic and adjusting the maximum weighted degree constraint based on results of the greedy heuristic.
2. The method of claim 1 , wherein the weight is assigned based at least in part on a degree of contention for resources between a pair of APs.
3. The method of claim 1 , wherein the weight is assigned based at least in part on a degradation of signal-to-interference-plus-noise ratio (SINR) caused by a first AP to a second AP.
4. The method of claim 1 , wherein the weight is assigned based at least in part on whether a first AP is a hidden node with respect to a second AP.
5. The method of claim 1 , wherein the weight is assigned based at least in part on a load associated with an AP.
6. The method of claim 1 , wherein the weight is assigned based on backoff behaviors between APs and their clients.
7. The method of claim 1 , wherein the weight is assigned based on the channel bandwidth assigned to an AP.
8. The method of claim 1 , wherein the function comprises a sum of the weighted edges of the conflict graph.
9. The method of claim 1 , wherein the plurality of Wi-Fi parameters comprises one or more of the following: transmit power parameters, channel allocation parameters, carrier sense threshold (CST) parameters, and multiple-input multiple-output (MIMO) antenna parameters.
10. The method of claim 9 , wherein the plurality of Wi-Fi parameters are jointly optimized.
11. The method of claim 9 , wherein the plurality of Wi-Fi parameters comprises CST parameters, and wherein the adjustments to the CST parameters are further based on one or more of the following: SINR, AP density, client data requirements, and propagation conditions of APs sharing the same channel.
12. The method of claim 1 , wherein a report received from an AP comprises measurement data collected by the AP, the measurement data comprising one or more of the following: receive signal strength indication (RSSI) of packets sent by another AP or another client, noise level of packets sent by another AP or another client, and signal-to-noise ratio (SNA) of packets sent by another AP or another client.
13. The method of claim 1 , wherein a report received from an AP comprises information corresponding to the AP, the information comprising one or more of the following: a MAC address of the AP, a current channel assigned to the AP, load information of the AP, and MAC addresses of clients associated with the AP.
14. A system for dynamically adjusting Wi-Fi parameters of a plurality of access points (APs), comprising:
an interface configured to receive reports from the plurality of APs;
a processor configured to:
create a conflict graph, comprising:
creating a plurality of vertices of the conflict graph, each vertex corresponding to one of the plurality of APs;
determining that there is a conflict between at least some of the pairs of APs based at least in part on the received reports;
connecting an edge between each of the at least some of the pairs of APs; and
assigning a weight to each of the edges of the conflict graph; and
search for adjustments to a plurality of Wi-Fi parameters that minimize a function of the weighted edges of the conflict graph using an optimization technique, wherein the search is subject to a maximum weighted degree constraint, wherein the maximum weighted degree constraint limits the weighted degree of each AP to a predetermined threshold, wherein the maximum weighted degree constraint is determined based at least in part on a greedy heuristic, wherein the determination of the maximum weighted degree constraint comprises:
initializing the maximum weighted degree constraint to a value within a lower bound and an upper bound; and
iteratively searching for adjustments to the plurality of Wi-Fi parameters that approximately minimize the function of the weighted edges of the conflict graph using the greedy heuristic and adjusting the maximum weighted degree constraint based on results of the greedy heuristic; and
a memory coupled to the processor and configured to provide the processor with instructions.
15. The system of claim 14 , wherein the weight is assigned based at least in part on a degree of contention for resources between a pair of APs.
16. The system of claim 14 , wherein the weight is assigned based at least in part on a degradation of signal-to-interference-plus-noise ratio (SINR) caused by a first AP to a second AP.
17. The system of claim 14 , wherein the weight is assigned based at least in part on whether a first AP is a hidden node with respect to a second AP.
18. The system of claim 14 , wherein the weight is assigned based at least in part on a load associated with an AP.
19. The system of claim 14 , wherein the weight is assigned based on backoff behaviors between APs and their clients.
20. The system of claim 14 , wherein the weight is assigned based on the channel bandwidth assigned to an AP.
21. The system of claim 14 , wherein the function comprises a sum of the weighted edges of the conflict graph.
22. The system of claim 14 , wherein the plurality of Wi-Fi parameters comprises one or more of the following: transmit power parameters, channel allocation parameters, carrier sense threshold (CST) parameters, and multiple-input multiple-output (MIMO) antenna parameters.
23. The system of claim 22 , wherein the plurality of Wi-Fi parameters are jointly optimized.
24. The system of claim 22 , wherein the plurality of Wi-Fi parameters comprises CST parameters, and wherein the adjustments to the CST parameters are further based on one or more of the following: SINR, AP density, client data requirements, and propagation conditions of APs sharing the same channel.
25. The system of claim 14 , wherein a report received from an AP comprises measurement data collected by the AP, the measurement data comprising one or more of the following: receive signal strength indication (RSSI) of packets sent by another AP or another client, noise level of packets sent by another AP or another client, and signal-to-noise ratio (SNA) of packets sent by another AP or another client.
26. The system of claim 14 , wherein a report received from an AP comprises information corresponding to the AP, the information comprising one or more of the following: a MAC address of the AP, a current channel assigned to the AP, load information of the AP, and MAC addresses of clients associated with the AP.
27. A computer program product for dynamically adjusting Wi-Fi parameters of a plurality of access points (APs), the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:
receiving reports from the plurality of APs;
creating a conflict graph, comprising:
creating a plurality of vertices of the conflict graph, each vertex corresponding to one of the plurality of APs;
determining that there is a conflict between at least some of the pairs of APs based at least in part on the received reports;
connecting an edge between each of the at least some of the pairs of APs;
assigning a weight to each of the edges of the conflict graph; and
storing the conflict graph; and
searching for adjustments to a plurality of Wi-Fi parameters that minimize a function of the weighted edges of the conflict graph using an optimization technique, wherein the search is subject to a maximum weighted degree constraint, wherein the maximum weighted degree constraint limits the weighted degree of each AP to a predetermined threshold, wherein the maximum weighted degree constraint is determined based at least in part on a greedy heuristic, wherein the determination of the maximum weighted degree constraint comprises:
initializing the maximum weighted degree constraint to a value within a lower bound and an upper bound; and
iteratively searching for adjustments to the plurality of Wi-Fi parameters that approximately minimize the function of the weighted edges of the conflict graph using the greedy heuristic and adjusting the maximum weighted degree constraint based on results of the greedy heuristic.