Cross-layer wireless bit rate adaptation

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 2X higher throughput than popular frame-level protocols such as SampleRate and RRAA. It also achieves 20% more throughput than an SNR-based protocol trained on the operating environment, and up to 4X 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.National Science Foundation (U.S.) (Grant CNS-0721702)National Science Foundation (U.S.) (Grant CNS-0520032)Foxconn International Holdings Ltd

S-PRAC: Fast Partial Packet Recovery with Network Coding in Very Noisy Wireless Channels

Well-known error detection and correction solutions in wireless communications are slow or incur high transmission overhead. Recently, notable solutions like PRAC and DAPRAC, implementing partial packet recovery with network coding, could address these problems. However, they perform slowly when there are many errors. We propose S-PRAC, a fast scheme for partial packet recovery, particularly designed for very noisy wireless channels. S-PRAC improves on DAPRAC. It divides each packet into segments consisting of a fixed number of small RLNC encoded symbols and then attaches a CRC code to each segment and one to each coded packet. Extensive simulations show that S-PRAC can detect and correct errors quickly. It also outperforms DAPRAC significantly when the number of errors is high

Experimental Evaluation of Large Scale WiFi Multicast Rate Control

WiFi multicast to very large groups has gained attention as a solution for multimedia delivery in crowded areas. Yet, most recently proposed schemes do not provide performance guarantees and none have been tested at scale. To address the issue of providing high multicast throughput with performance guarantees, we present the design and experimental evaluation of the Multicast Dynamic Rate Adaptation (MuDRA) algorithm. MuDRA balances fast adaptation to channel conditions and stability, which is essential for multimedia applications. MuDRA relies on feedback from some nodes collected via a light-weight protocol and dynamically adjusts the rate adaptation response time. Our experimental evaluation of MuDRA on the ORBIT testbed with over 150 nodes shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of receivers while meeting quality requirements. MuDRA can support multiple high quality video streams, where 90% of the nodes report excellent or very good video quality

Capacity Estimation for Error Correction Code-based Embedding in Adaptive Rate Wireless Communication Systems

In this paper, we explore the performance of error correction code-based embedding in adaptive rate wireless communication systems. We first develop a model to illustrate the relationship between the selected modulation and coding scheme index, the current channel state, and the embedding capacity. Extensive simulations facilitate the development of expressions to describe the estimated embedding capacity for the proposed scheme when implemented within the single carrier physical layer of the IEEE 802.11ad, directional multi-Gigabit standard. We further identify and characterize various types of distortion and describe additional constraints that may serve to reduce the available embedding margin and overall embedding capacity

Wilis: Architectural Modeling of Wireless Systems

The performance of a wireless system depends on the wireless channel as well as the algorithms used in the transceiver pipelines. Because physical phenomena affect transceiver pipelines in difficult to predict ways, detailed simulation of the entire transceiver system is needed to evaluate even a single processing block. Further, some protocol validations require simulation of rare events (say, 1 bit error in 109 bits), which means the protocol must simulate for a long enough time for such events to materialize. This requirement coupled with the heavy computation typical of most physical-layer processing, rules out pure software solutions. In this paper we describe WiLIS, an FPGA-based hybrid hardware-software system designed to facilitate the development of wireless protocols. We then use WiLIS to evaluate several microarchitectures for measuring very low bit-error rates (BER). We demonstrate, for the first time, that the recently proposed SoftPHY can be implemented efficiently in hardware

Optimal Rate Sampling in 802.11 Systems

In 802.11 systems, Rate Adaptation (RA) is a fundamental mechanism allowing transmitters to adapt the coding and modulation scheme as well as the MIMO transmission mode to the radio channel conditions, and in turn, to learn and track the (mode, rate) pair providing the highest throughput. So far, the design of RA mechanisms has been mainly driven by heuristics. In contrast, in this paper, we rigorously formulate such design as an online stochastic optimisation problem. We solve this problem and present ORS (Optimal Rate Sampling), a family of (mode, rate) pair adaptation algorithms that provably learn as fast as it is possible the best pair for transmission. We study the performance of ORS algorithms in both stationary radio environments where the successful packet transmission probabilities at the various (mode, rate) pairs do not vary over time, and in non-stationary environments where these probabilities evolve. We show that under ORS algorithms, the throughput loss due to the need to explore sub-optimal (mode, rate) pairs does not depend on the number of available pairs, which is a crucial advantage as evolving 802.11 standards offer an increasingly large number of (mode, rate) pairs. We illustrate the efficiency of ORS algorithms (compared to the state-of-the-art algorithms) using simulations and traces extracted from 802.11 test-beds.Comment: 52 page