Cross-layer wireless bit rate adaptation

VutukuruMythili,; BalakrishnanHari,; JamiesonKyle,

doi:10.1145/1594977.1592571

Cited by 166 publications

(160 citation statements)

References 24 publications

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“…Rate Adaptation: Rate adaptation has been one of the most popular research topics in WLANs [10], [1], [19] and new algorithms for 802.11n networks have been proposed [2], [5], [20], [21]. Although solutions for legacy clients have been effective, they fall short when applied in 802.11n OFDM-MIMO settings [5].…”

Section: Related Workmentioning

confidence: 99%

Joint rate and channel width adaptation for 802.11 MIMO wireless networks

Deek

García-Villegas

Belding

et al. 2013

2013 IEEE International Conference on Sensing, Communications and Networking (SECON)

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Abstract-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 selecting the right transmission rate. 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, we propose ARAMIS (Agile Rate Adaptation for MIMO Systems), a standard-compliant, closed-loop RA solution that jointly adapts rate and bandwidth. ARAMIS adapts transmission rates on a per-packet basis; we believe it is the first 802.11n RA algorithm that simultaneously adapts rate and channel width. We have implemented ARAMIS 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.

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Section: Related Workmentioning

confidence: 99%

Joint rate and channel width adaptation for 802.11 MIMO wireless networks

Deek

García-Villegas

Belding

et al. 2013

2013 IEEE International Conference on Sensing, Communications and Networking (SECON)

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“…In [12], the authors use probing packets to estimate the channel status. In [17], the authors propose using bit error rates to control data sending rates. In [18], the authors suggest using the error vector magnitude (EVM) of orthogonal frequency division multiplexing (OFDM) symbols to control data sending rates.…”

Section: Related Workmentioning

confidence: 99%

SINR-Based MCS Level Adaptation in CSMA/CA Wireless Networks to Embrace IoT Devices

Cho

2017

Symmetry

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This paper presents an automatic modulation and coding scheme (MCS) level adaptation algorithm to embrace Internet of Things (IoT) devices by improving the area spectral efficiency of carrier-sense multiple access with collision avoidance (CSMA/CA) wireless networks. In the proposed algorithm, senders of CSMA/CA wireless networks use the signal to interference plus noise ratio of acknowledgment frames from their receivers to estimate channel statuses between the senders and the receivers. Using the estimated channel status of each receiver, senders control sending rates of traffic by adjusting MCS levels of packets destined for each receiver. We use Poisson point processes (PPPs) to model the locations of participating nodes (i.e., access points and wireless devices) in a given area. We evaluate the effectiveness of the proposed algorithm using an event-driven ns-2 simulator for various PPP densities of access points and wireless devices.

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“…softrate [21] uses BER of received packets to estimate bitrate that channel can support. AccuRate in [19] leverages channel distortion to estimate the best rate.…”

Section: A Rate Adaptation Based On 2d Modulation Schemesmentioning

confidence: 99%

TiM: Fine-Grained Rate Adaptation in WLANs

Wang¹,

Zhang

et al. 2014

2014 IEEE 34th International Conference on Distributed Computing Systems

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Abstract-Channel condition varies frequently in wireless networks. To achieve good performance, devices need rate adaptation. In rate adaptation, choosing proper modulation schemes based on channel conditions is vital to the transmission performance. However, due to the natural character of discrete modulation types and continuous varied link conditions, we cannot make a one-to-one mapping from modulation schemes to channel conditions. This matching gap causes either over-select or underselect modulation schemes which limits throughput performance. To fill-in the gap, we propose TiM (Time-line Modulation), a novel 3-Dimensional modulation scheme by adding time dimension into current amplitude-phase domain schemes. With estimation of channel condition, TiM changes base-band data transmission time by artificially interpolating values between original data points without changing amplitude-phase domain modulation type. We implemented TiM on USRP2 and conducted comprehensive simulations. Results show that, compared with rate adaptation choosing from traditional modulation schemes, TiM can improve channel utilization up to 200%.

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Cross-layer wireless bit rate adaptation

Cited by 166 publications

References 24 publications

Joint rate and channel width adaptation for 802.11 MIMO wireless networks

Joint rate and channel width adaptation for 802.11 MIMO wireless networks

SINR-Based MCS Level Adaptation in CSMA/CA Wireless Networks to Embrace IoT Devices

TiM: Fine-Grained Rate Adaptation in WLANs

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