Distributed Spectrum Assignment for Home WLANs

We consider the problem of jointly allocating chan- nel center frequencies and bandwidths for IEEE 802.11 wireless LANs (WLANs). The bandwidth used on a link affects sig- nificantly both the capacity experienced on this link and the interference produced on neighboring links. Therefore, when jointly assigning both center frequencies and channel widths, there is a trade-off between interference mitigation and the potential capacity offered on each link. We study this trade- off and we present SAW (spectrum assignment for WLANs), a decentralized algorithm that finds efficient configurations. SAW is tailored for 802.11 home networks. It is distributed, online and transparent. It does not require a central coordinator and it constantly adapts the spectrum usage without disrupting network traffic. A key feature of SAW is that the access points (APs) need only a few out-of-band measurements in order to make spectrum allocation decisions. Despite being completely decentralized, the algorithm is self-organizing and provably converges towards efficient spectrum allocations. We evaluate SAW using both simulation and a deployment on an indoor testbed composed of off-the-shelf 802.11 hardware. We observe that it dramatically increases the overall network efficiency and fairness

Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications

A channel allocation algorithm for OSA-Enabled IEEE 802.11 WLANs

Channel allocation problem is a major challenge in wireless local area networks (WLANs), especially in dense deployments of access points (APs) where congestion of the unlicensed spectrum bands (i.e., ISM bands) could undermine achieved network performance. This paper analyses the possibility to alleviate congestion of the ISM band by allowing some APs to use additional channels located in licensed bands in an opportunistic manner whenever licensee services (i.e., primary users) are not affected. Availability of these additional channels in licensed bands is assumed not to be the same for all the APs. Based on this assumption, we formulate the problem for the channel assignment as a Binary Linear Programming (BLP) problem, which allows us to obtain an optimal solution despite an elevated execution time. We also develop a heuristic method based on building a Minimum Spanning Tree (MST) graph attending to interference conditions that is able to find nearoptimal solutions with a shorter execution time. Results are provided to assess the benefits of such a proposal under different WLAN deployment situations and primary channel availability conditions.Postprint (published version

Attention to Wi-Fi Diversity: Resource Management in WLANs with Heterogeneous APs

Many home networks integrate a small number (typically 2-4) of Wi-Fi Access Points (APs), with heterogeneous characteristics: different 802.11 variants, capabilities and security schemes. This paper proposes the consideration of these specific characteristics in order to improve the management of network resources. Three use cases are presented in order to showcase the potential benefits. By the use of a user-space AP, which works in coordination with a controller, the network is able to assign each connected station to the AP that best fits with its characteristics. The system also manages security, avoiding the need of adding specific elements for authentication, encryption or decryption. Extensions are proposed to an existing protocol that defines the communication between the AP and the controller, in order to communicate and store the specific characteristics of each AP and end device. This includes new association and handoff schemes that do not introduce any additional delay. The system has been implemented in a real environment, and a battery of tests has been run using three hardware platforms of different characteristics. The results show that handoffs between bands are possible, and estimate the processing delays, the Round-Trip Time and the handoff delay, which is small enough in order not to produce any significant disruption to the user (10-50 ms). Finally, the scenarios of interest have been replicated in a simulation environment, showing that significant benefits can be achieved if the specific characteristics of each AP and station are considered