【正文】 s points (APs) on a referen access point, resulting in higher throughput. We implement ansimulate our algorithm using two versions (I: pick rand an II: pick ?rst) and different number of APs (4, 9, 16, and 25. Analysis of our algorithm shows an improvement by a factor 4 (by lowering the total interference on an AP by 6 dBm .average) over default settings of having all APs use the sam channel. As the number of APs is increased in a given servi area, dynamic channel assignment bees crucial。 otherwioverlapping channel interference bees a limiting when using different models. Also, a frequency separation of 3 or 4 channels between APs is suitable. In [4], the authors assign frequencies to APs using an algorithm that has an exponential putational plexity. To overe the putationally intensive algorithm, the authors also use a greedy algorithm that is close to optimal but may not yield the optimal frequency assignment for a given WLAN. In [5], the authors propose techniques to improve the usage of wireless spectrum in WLANs. The authors emphasize that the use of a least congested channel search for assigning new channels for interfering APs is not ef?cient with continued growth of WLANs.I. INTRODUCTIONTremendous growth and wide usage of IEEE with increasing user access has raised issues like quality of service, channel interference, and network load increase in deployment of access points (APs) leads tocochannel interference from neighboring APs degrading thenetwork throughput. Issues related to resource managementand interference impede the performance of assignment [1] is a major problem in designing wireless networks. All APs share the same frequency, which leads to interference that should be minimized and avoided if necessary, using ef?cient assignment of channels. In [1],the authors formulate an integer linear programming problem to optimize the channel assignment for hot spot service ar eas. The objective of their optimization is to minimize the maximum channel utilization, yielding higher throughput. In [2], the authors discuss the implementation of IEEE based WLANs for enterprise customers with limitations like performance under heavy load, deployment issues, and network management. The authors suggest using dynamic resource management over static radio resource management to improve performance of large scale WLANs. Analysis of channel assignment for using radio interference is done in [3]. Experimental results show that performance differs with changing environmental conditions and when using different models. Also, a frequency separation of 3 or 4 channels between APs is suitable. In [4] the authors assign frequencies to APs using an algorithm that has an exponential putational plexity. To overe the putationally intensive algorithm, the authors also use a greedy algorithm that is close to optimal but may not yield the optimal frequency assignment for a given WLAN. In [5], the authors propose techniques to improve the usage of wireless spectrum in WLANs. The authors emphasize that the use of a least congested channel search for assigning new channels for interfering APs is not ef?cient with continued growth of WLANs.Our contributions are twofolds. First, we develop a math ematical model that captures the amount of interference between oerlapping channels for IEEE WLAN , we design a dynamic channel allocation algorithm by minimizing channel interference between APs. Assigningoptimal channels to APs is a crucial process for overall performance. Our algorithm assigns channels in a way that minimizes overlapping channel interference resulting in higher throughput. Numerical results are presented and analyzed for4, 9, 16, and 25 APs.The remainder of this paper is organized as follows. Channelnterference in is presented in Section II. In SectionII, we de?ne our overlapping channel interference factor. Our ynamic channel assignment algorithm is described in Section V. Numerical results are presented in Section V, and ?nally ection VI concludes the paper.II. OVERLAPPING CHANNEL INTERFERENCE[6], [7]. In , transmissions between APs and demand clusters do not use a single frequency. Instead, the frequencies are divided into 14 channels, and use a modulation technique,direct sequence spread spectrum, to spread the transmission over multiple channels for effective uses of the frequency spectrum. Channel 1 is assigned to GHz. There is 5MHz separation between the channels. Thus,channel 14 is assigned to GHz. In the United States, channels 111 are used. Europe uses channels 113. Japan uses channels 114. An , an Channels should be assigned to APs such that overlapping channel interference is minimized. Channels are reused because of limited availability. The same channel should be assigned to two APs, which are located far enough apart, if the overlapping channel interference signal detected by each AP is less than a given threshold.Use of overlapping channels degrades network in causes APs and stations to send frames over and over again to increase the odds of successful transmission. Typically, if devices were to send one copy of a frame, data is transmitted at 11 Mbps (54 Mbps for ). However, if the ef?ciency were to drop to 50%, for instance, because of interference, the devices would still be transmitting at 11 Mbps, but it would be duplicating each frame, making the effective throughput Mbps. Therefore, networks will have a signi?cant decrease in network performance because of interference.III. OVERLAPPING CHANNEL INTERFERENCE FACTORWe model overlapping channel interference by de?ning an overlapping channel interference factor, wij ,to be therelative percentage increase in interference as a result of two APs i and j using overlapping channels. Thus overlapping channels assigned to APs must be chosen instance, if channel 1 is assigned to AP i and channel 1 is also assigned to AP j, the overlapping channel interference factor between AP i and AP j, wij , is or 1