Abstract — We propose an efficient client-based approach for channel management (channel assignment and load balancing) in 802.11-based WLANs that lead to better usage of the wireless spectrum. This approach is based on a “conflict set coloring ” formulation that jointly performs load balancing along with channel assignment. Such a formulation has a number of advantages. First, it explicitly captures interference effects at clients. Next, it intrinsically exposes opportunities for better channel re-use. Finally, algorithms based on this formulation do not depend on specific physical RF models and hence can be applied efficiently to a wide-range of in-building as well as outdoor scenarios. We have performed extensive packet-level simulations and measurements on a deployed wireless testbed of 70 APs to validate the performance of our proposed algorithms. We show that in addition to single network scenarios, the conflict set coloring formulation is well suited for channel assignment where multiple wireless networks share and contend for spectrum in the same physical space. Our results over a wide range of both simulated topologies and in-building testbed experiments indicate that our approach improves application level performance at the clients by upto three times (and atleast 50%) in comparison to current best-known techniques. I.

The importance of spatial reuse in wireless ad-hoc networks has been long recognized as a key to improving the network capacity. One can increase the level of spatial reuse by either reducing the transmit power or increasing the carrier sense threshold (thereby reducing the carrier sense range). On the other hand, as the transmit power decreases or the carrier sense threshold increases, the SINR decreases as a result of the smaller received signal or the increased interference level. Consequently, the data rate sustained by each transmission may decrease. This leads naturally to the following questions: (1) How can the trade-off between the increased level of spatial reuse and the decreased data rate each node can sustain be quantified? In other words, is there an optimal range of transmit power/carrier sense threshold in which the network capacity is maximized? (2) What is the relation between

Wireless 802.11 hotspots have grown in an uncoordinated fashion with highly variable deployment densities. Such uncoordinated deployments, coupled with the difficulty of implementing coordination protocols, has often led to conflicting configurations (e.g., in choice of transmission power and channel of operation) among the corresponding Access Points (APs). Overall, such conflicts cause both unpredictable network performance and unfairness among clients of neighboring hotspots. In this paper, we focus on the fairness problem for uncoordinated deployments. We study this problem from the channel assignment perspective. Our solution is based on the notion of channel-hopping, and meets all the important design considerations for control methods in uncoordinated deployments — distributed in nature, minimal to zero coordination among APs belonging to different hotspots, simple to implement, and interoperable with existing standards. In particular,

We argue that carrier sense in 802.11 and other wireless protocols leads to scheduling decisions that are overly pessimistic and hence waste capacity. As an alternative, we propose interference cancellation, in which simultaneous signals are modeled and decoded together rather than treating all but one as random noise. This method greatly expands the conditions under which overlapping transmissions can be successfully received, even by a single receiver. We demonstrate the practicality of these better receivers via a proof-of-concept experiment with USRP software radios. We argue that supporting concurrent transmissions enables new and more effective wireless MACs in which carrier sense is disabled.

Efficient usage of available capacity in wireless mesh networks is critical. Capacity is wasted due to the exposed terminal problem. In this paper, we propose a solution to mitigate the exposed terminal problem in static IEEE 802.11-based mesh networks, thereby improving the spatial reuse of the medium and increasing network throughput. Our solution is complementary to previously-proposed solutions that adjust the carrier-sense range for improved spatial reuse. The proposed solution consists of two phases. In the first phase, exposed links in the mesh topology are detected through an offline training process. Coordination of simultaneous transmissions over exposed links is then done in the second phase through the use of Request-To-Send-Simultaneously (RTSS) and Clear-To-Send-Simultaneously (CTSS) messages, which are added to the MAC protocol. Our solution preserves the distributed nature of the MAC protocol and does not require time synchronization between nodes. We present a simulation-based evaluation that demonstrates that the proposed solution effectively improves capacity usage and network throughput in representative topologies and traffic scenarios.

Carrier sense is often used to regulate concurrency in wireless medium access control (MAC) protocols, balancing interference protection and spatial reuse. Carrier sense is known to be imperfect, and many improved techniques have been proposed. Is the search for a replacement justified? This paper presents a theoretical model for average case two-sender carrier sense based on radio propagation theory and Shannon capacity. Analysis using the model shows that carrier sense performance is surprisingly close to optimal for radios with adaptive bitrate. The model suggests that hidden and exposed terminals usually cause modest reductions in throughput rather than dramatic decreases. Finally, it is possible to choose a fixed sense threshold which performs well across a wide range of scenarios, in large part due to the role of the noise floor. Experimental results from an indoor 802.11 testbed support these claims.

With the proliferation of wireless local area network (WLAN) technologies, wireless Internet access via public hotspots will become a necessity in the near future. In outdoor areas where the installation of a large number of wired access points is practically or economically infeasible, mobile users located at the edge of the network communicate with the access point at a very low rate and in turn waste network resources. In this work, we promote the use of tetherless relay points (TRPs) to improve the throughput of a WLAN in such environments. We first provide a high level description on how to integrate TRPs in a multi-rate WLAN architecture. We then propose an integer-programming optimization formulation and an iterative approach to compute the best placement of a fixed number of TRPs. Finally, we show in numerical analysis, through a case study based on relay-enabled rate adaptation and IEEE 802.11-like multi-rate physical model with Rayleigh fading, that for a wide range of system parameters, significant performance gain can be achieved when TRPs are strategically installed in the network.

Abstract—In this paper, we describe a protocol that manages the transmission power of 802.11 devices to maximize the performance of nodes within an area with a dense concentration of 802.11 networks. We show that it is possible to calculate the ratio between the transmit power of different nodes that maximizes overall network capacity. We present a protocol that implements a distributed version of our transmission power setting algorithm. Our protocol also tunes carrier sense thresholds to ensure that simultaneous transmissions occur when possible. Our evaluation of this protocol using the OPNET simulator shows that it improves network capacity by 22 % to 87 % over only adjusting carrier sense and by 2 % to 67 % over using the minimum possible transmit power level. I.

Abstract — The capacity problem in wireless mesh networks can be alleviated by equipping the mesh routers with multiple radios tuned to non-overlapping channels. However, channel assignment presents a challenge because co-located wireless networks are likely to be tuned to the same channels. The resulting increase in interference can adversely affect performance. This paper presents an interference-aware channel assignment algorithm and protocol for multi-radio wireless mesh networks that address this interference problem. The proposed solution intelligently assigns channels to radios to minimize interference within the mesh network and between the mesh network and co-located wireless networks. It utilizes a novel interference estimation technique implemented at each mesh router. An extension to the conflict graph model, the multi-radio conflict graph, is used to model the interference between the routers. We demonstrate our solution’s practicality through the evaluation of a prototype implementation in a IEEE 802.11 testbed. We also report on an extensive evaluation via simulations. In a sample multi-radio scenario, our solution yields performance gains in excess of 40% compared to a static assignment of channels. I.

The availability of spectrum resources has not kept pace with wireless network popularity. As a result, data transfer performance is often limited by the number of devices interfering on the same frequency channel within an area. In this paper, we introduce a protocol that manages the transmission power and CCA threshold of 802.11 devices to maximize network performance. The protocol is based on the observation that for a pair of interfering wireless links, it is possible to calculate the ratio of the transmit power of the two senders that maximizes overall network capacity. We first present an algorithm that extends this result for dense clusters of nodes and then describe a distributed protocol that implements the transmission power setting algorithm and CCA tuning mechanism. Finally, we describe an implementation of the project in Linux. It uses commercial 802.11 cards and addressed several practical challenges such as protocol stability and calibration. Our experimental evaluation using an 8 node testbed shows that our protocol works well in practice and can improve the performance over default configurations by more than 200%. We also use OPNET simulations to evaluate larger topologies with different node densities.