Existing Rate Adaptation Algorithms Research Articles

Non-Stationary Bandit Strategy for Rate Adaptation With Delayed Feedback

Rate adaptation is an efficient mechanism to utilize the channel capacity by adjusting the modulation and coding scheme in a dynamic wireless environment. The channel feedback, such as acknowledgment/negative acknowledgment (ACK/NACK) messages or the channel measurement such as received signal strength indicator (RSSI) can be applied to the rate adaptation. Existing rate adaptation algorithms are mainly driven by heuristics. They can not achieve satisfactory transmission rates in the time-varying environment. In this paper, we focus on the rate adaptation problem in a time-division duplex (TDD) system. A multi-armed bandit (MAB) strategy is applied to learn the changes of the channel condition from both RSSI and ACK/NACK signals. A discounted upper confidence bound based rate adaptation (DUCB-RA) algorithm is proposed. We show that the performance of the proposed algorithm is converged to the optimal with mathematical proofs. Simulation results demonstrate that the proposed algorithm can adapt to the time-varying channel and achieve better transmission throughput compared to existing rate adaptation algorithms.

A practical framework for 802.11 MIMO rate adaptation

The emergence of MIMO antennas and channel bonding in 802.11n wireless networks has resulted in a huge leap in capacity compared with legacy 802.11 systems. This leap, however, adds complexity to optimizing transmission. Not only does the appropriate data rate need to be selected, but also the MIMO transmission technique (e.g., Spatial Diversity or Spatial Multiplexing), the number of streams, and the channel width. Incorporating these features into a rate adaptation (RA) solution requires a new set of rules to accurately evaluate channel conditions and select the appropriate transmission setting with minimal overhead. To address these challenges, our contributions in this work are two-fold. First, we propose a practical link metric that accurately captures channel conditions in MIMO 802.11n environments, and we call this metric diffSNR. Using diffSNR captured from real testbed environments, we build performance models that accuractely predict link quality in 95.5% of test cases. Practicality and deployability are guaranteed with diffSNR as it can be measured on all off-the-shelf MIMO WiFi chipsets. Second, we propose ARAMIS (Agile Rate Adaptation for MIMO Systems), a standard-compliant, closed-loop RA solution that jointly adapts rate and bandwidth, and we utilize the diffSNR-based 802.11n performance models within ARAMIS’s framework. ARAMIS adapts transmission rates on a per-packet basis; we believe it is the first closed-loop, 802.11 RA algorithm that simultaneously adapts rate and channel width. We have implemented ARAMIS with diffSNR on Atheros-based devices and deployed it on our 15-node testbed. Our experiments show that ARAMIS accurately adapts to a wide variety of channel conditions with negligible overhead. Furthermore, ARAMIS outperforms existing RA algorithms in 802.11n environments with up to a 10-fold increase in throughput.

Throughput‐based rate adaptation algorithm for IEEE 802.11 vehicle networks

A key problem with IEEE 802.11 technology is adaptation of the transmission rates to the changing channel conditions, which is more challenging in vehicular networks. Although rate adaptation problem has been extensively studied for static residential and enterprise network scenarios, there is little work dedicated to the IEEE 802.11 rate adaptation in vehicular networks. Here, the authors are motivated to study the IEEE 802.11 rate adaptation problem in infrastructure-based vehicular networks. First of all, the performances of several existing rate adaptation algorithms under vehicle network scenarios, which have been widely used for static network scenarios, are evaluated. Then, a new rate adaptation algorithm is proposed to improve the network performance. In the new rate adaptation algorithm, the technique of sampling candidate transmission modes is used, and the effective throughput associated with a transmission mode is the metric used to choose among the possible transmission modes. The proposed algorithm is compared to several existing rate adaptation algorithms by simulations, which shows significant performance improvement under various system and channel configurations. An ideal signal-to-noise ratio (SNR)-based rate adaptation algorithm in which accurate channel SNR is assumed to be always available is also implemented for benchmark performance comparison.

Enhancing Voice over WLAN via Rate Adaptation and Retry Scheduling

Today, voice over IP (VoIP) service is emerging as a popular and important application in wireless local area networks (WLANs). While rate adaptation (or link adaptation) has been identified as a key factor determining the performance of WLANs, we have observed that most (if not all) rate adaptation algorithms have been developed to improve the throughput of data traffic, not the quality of service (QoS) of VoIP traffic. Accordingly, in this paper, we investigate the characteristics of VoIP traffic and the limitations of state-of-the-art rate adaptation algorithms, and then enhance the QoS of voice over WLAN (VoWLAN) by ameliorating the existing rate adaptation algorithms. Specifically, we design fast decrease to control the transmission rate of retransmissions, and retry scheduling to avoid the deep fading of the wireless channel as well as hidden terminal interference. We comparatively evaluate the QoS of the revised rate adaptation algorithms via ns-3 simulations and MadWiFi implementations in various communication environments, and demonstrate that the proposed schemes improve the R-score performance by up to 80 percent depending on the network scenarios.

A Performance Evaluation for Rate Adaptation Algorithms in IEEE 802. 11 Wireless Networks

The wireless LAN standards IEEE 802.11 (a/b/g) provides multi-rates capabilities. To achieve high network performance, devices need to adapt their transmission rate dynamically under varying conditions. Rate adaption algorithm is a critical component of their performance, only very a few algorithms have been published and the differences between their mechanisms have been publicly discussed. In this paper rate adaption algorithms categorized according to the metric that sender and/or receiver used to calculate the best bit rate uses to transmission date. In addition, a comparative study conducted in IEEE 802.11-based ad-hoc networks of most existing rate adaptation algorithms. General Terms Performance, Algorithms, Simulation, Wireless Network

Vehicular wifi access and rate adaptation

Vehicular WiFi access is distinct in two respects, (i) continuous mobility of clients and (ii) possibility of predictable link quality. As part of this study, we aim to comprehensively evaluate existing rate adaptation algorithms in real environments. Further, if required, we aim to develop a simple, low-overhead rate adaptation algorithm suited for vehicular WiFi access.

SARA: Stochastic Automata Rate Adaptation for IEEE 802.11 Networks

Existing rate adaptation algorithms can broadly be classified under two categories: (a) signal to noise ratio measurement based and (b) statistical count based. While the former suffers from inaccurate estimations, the latter utilizes pre-defined thresholds for dynamically varying the rate. In this paper, we first analyze the impact of transmission rate on the performance of a wireless link as the performance may either improve or deteriorate with increasing transmission rates. Based on this observation, we then propose stochastic automata rate adaptation algorithm (SARA). SARA is inspired by stochastic learning automata (SLA), a machine learning technique for adaptation in random environments. SARA assigns a selection probability to each of the transmission rates. It then randomly selects a rate for a transmission attempt and dynamically updates the probabilities based on the obtained feedback from the receiver (ACK/NACK), thereby obviating the need for explicit channel estimation or predefined thresholds. As opposed to the previous work, SARA is ideally suited for both stationary and non-stationary channel environments and is fully compatible with the existing IEEE 802.11 MAC standard. We compare the performance of our proposed protocol with automatic rate fallback (ARF) thoroughly and adaptive ARF (AARF) and other existing protocols, under different channel scenarios.