This paper presents SoftRate, a wireless bit rate adaptation protocol that is responsive to rapidly varying channel conditions. Unlike previous work that uses either frame receptions or signal-to-noise ratio (SNR) estimates to select bit rates, SoftRate uses confidence information calculated by the physical layer and exported to higher layers via the SoftPHY interface to estimate the prevailing channel bit error rate (BER). Senders use this BER estimate, calculated over each received packet (even when the packet has no bit errors), to pick good bit rates. SoftRate's novel BER computation works across different wireless environments and hardware without requiring any retraining. SoftRate also uses abrupt changes in the BER estimate to identify interference, enabling it to reduce the bit rate only in response to channel errors caused by attenuation or fading. Our experiments conducted using a software radio prototype show that SoftRate achieves 2× higher throughput than popular frame-level protocols such as SampleRate [4] and RRAA [24]. It also achieves 20% more throughput than an SNR-based protocol trained on the operating environment, and up to 4× higher throughput than an untrained SNR-based protocol. The throughput gains using SoftRate stem from its ability to react to channel variations within a single packet-time and its robustness to collision losses.

Dense 802.11 wireless networks present a pressing capacity challenge: users in proximity contend for limited unlicensed spectrum. Directional antennas promise increased capacity by improving the signal-to-interference-plus-noise ratio (SINR) at the receiver, potentially allowing successful decoding of packets at higher bit-rates. Many uses of directional antennas to date have directed high gain between two peers, thus maximizing the strength of the sender's signal reaching the receiver. But in an interference-rich environment, as in dense 802.11 deployments, directional antennas only truly come into their own when they explicitly null interference from competing concurrent senders. In this paper, we present Cone of Silence (CoS), a technique that leverages software-steerable directional antennas to improve the capacity of indoor 802.11 wireless networks by adaptively nulling interference. Using in situ signal strength measurements that account for the complex propagation environment, CoS derives custom antenna radiation patterns that maximize the strength of the signal arriving at an access point from a sender while nulling inteference from one or more concurrent interferers. CoS leverages multiple antennas, but requires only a single commodity 802.11 radio, thus avoiding the significant processing requirements of decoding multiple concurrent packets. Experiments in an indoor 802.11 deployment demonstrate that CoS improves throughput under interference.