84 research outputs found
Multi-level Turbo Decoding Assisted Soft Combining Aided Hybrid ARQ
Hybrid Automatic Repeat reQuest (ARQ) plays an essential role in error control. Combining the incorrectly received packet replicas in hybrid ARQ has been shown to reduce the resultant error probability, while improving the achievable throughput. Hence, in this contribution, multi-level turbo codes have been amalgamated both with hybrid ARQ and efficient soft combining techniques for taking into account the Log- Likelihood Ratios (LLRs) of retransmitted packet replicas. In this paper, we present a soft combining aided hybrid ARQ scheme based on multi-level turbo codes, which avoid the capacity loss of the twin-level turbo codes that are typically employed in hybrid ARQ schemes. More specifically, the proposed receiver dynamically appends an additional parallel concatenated Bahl, Cocke, Jelinek and Raviv (BCJR) algorithm based decoder in order to fully exploit each retransmission, thereby forming a multi-level turbo decoder. Therefore, all the extrinsic information acquired during the previous BCJR operations will be used as a priori information by the additional BCJR decoders, whilst their soft output iteratively enhances the a posteriori information generated by the previous decoding stages. We also present link- level Packet Loss Ratio (PLR) and throughput results, which demonstrate that our scheme outperforms some of the previously proposed benchmarks
A Rate-Compatible Sphere-Packing Analysis of Feedback Coding with Limited Retransmissions
Recent work by Polyanskiy et al. and Chen et al. has excited new interest in
using feedback to approach capacity with low latency. Polyanskiy showed that
feedback identifying the first symbol at which decoding is successful allows
capacity to be approached with surprisingly low latency. This paper uses Chen's
rate-compatible sphere-packing (RCSP) analysis to study what happens when
symbols must be transmitted in packets, as with a traditional hybrid ARQ
system, and limited to relatively few (six or fewer) incremental transmissions.
Numerical optimizations find the series of progressively growing cumulative
block lengths that enable RCSP to approach capacity with the minimum possible
latency. RCSP analysis shows that five incremental transmissions are sufficient
to achieve 92% of capacity with an average block length of fewer than 101
symbols on the AWGN channel with SNR of 2.0 dB.
The RCSP analysis provides a decoding error trajectory that specifies the
decoding error rate for each cumulative block length. Though RCSP is an
idealization, an example tail-biting convolutional code matches the RCSP
decoding error trajectory and achieves 91% of capacity with an average block
length of 102 symbols on the AWGN channel with SNR of 2.0 dB. We also show how
RCSP analysis can be used in cases where packets have deadlines associated with
them (leading to an outage probability).Comment: To be published at the 2012 IEEE International Symposium on
Information Theory, Cambridge, MA, USA. Updated to incorporate reviewers'
comments and add new figure
Backlog and Delay Reasoning in HARQ Systems
Recently, hybrid-automatic-repeat-request (HARQ) systems have been favored in
particular state-of-the-art communications systems since they provide the
practicality of error detections and corrections aligned with repeat-requests
when needed at receivers. The queueing characteristics of these systems have
taken considerable focus since the current technology demands data
transmissions with a minimum delay provisioning. In this paper, we investigate
the effects of physical layer characteristics on data link layer performance in
a general class of HARQ systems. Constructing a state transition model that
combines queue activity at a transmitter and decoding efficiency at a receiver,
we identify the probability of clearing the queue at the transmitter and the
packet-loss probability at the receiver. We determine the effective capacity
that yields the maximum feasible data arrival rate at the queue under
quality-of-service constraints. In addition, we put forward non-asymptotic
backlog and delay bounds. Finally, regarding three different HARQ protocols,
namely Type-I HARQ, HARQ-chase combining (HARQ-CC) and HARQ-incremental
redundancy (HARQ-IR), we show the superiority of HARQ-IR in delay robustness
over the others. However, we further observe that the performance gap between
HARQ-CC and HARQ-IR is quite negligible in certain cases. The novelty of our
paper is a general cross-layer analysis of these systems, considering
encoding/decoding in the physical layer and delay aspects in the data-link
layer
AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing
The enormous success of advanced wireless devices is pushing the demand for
higher wireless data rates. Denser spectrum reuse through the deployment of
more access points per square mile has the potential to successfully meet the
increasing demand for more bandwidth. In theory, the best approach to density
increase is via distributed multiuser MIMO, where several access points are
connected to a central server and operate as a large distributed multi-antenna
access point, ensuring that all transmitted signal power serves the purpose of
data transmission, rather than creating "interference." In practice, while
enterprise networks offer a natural setup in which distributed MIMO might be
possible, there are serious implementation difficulties, the primary one being
the need to eliminate phase and timing offsets between the jointly coordinated
access points.
In this paper we propose AirSync, a novel scheme which provides not only time
but also phase synchronization, thus enabling distributed MIMO with full
spatial multiplexing gains. AirSync locks the phase of all access points using
a common reference broadcasted over the air in conjunction with a Kalman filter
which closely tracks the phase drift. We have implemented AirSync as a digital
circuit in the FPGA of the WARP radio platform. Our experimental testbed,
comprised of two access points and two clients, shows that AirSync is able to
achieve phase synchronization within a few degrees, and allows the system to
nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC
and higher layer aspects of a practical deployment. To the best of our
knowledge, AirSync offers the first ever realization of the full multiuser MIMO
gain, namely the ability to increase the number of wireless clients linearly
with the number of jointly coordinated access points, without reducing the per
client rate.Comment: Submitted to Transactions on Networkin
Feedback Communication Systems with Limitations on Incremental Redundancy
This paper explores feedback systems using incremental redundancy (IR) with
noiseless transmitter confirmation (NTC). For IR-NTC systems based on {\em
finite-length} codes (with blocklength ) and decoding attempts only at {\em
certain specified decoding times}, this paper presents the asymptotic expansion
achieved by random coding, provides rate-compatible sphere-packing (RCSP)
performance approximations, and presents simulation results of tail-biting
convolutional codes.
The information-theoretic analysis shows that values of relatively close
to the expected latency yield the same random-coding achievability expansion as
with . However, the penalty introduced in the expansion by limiting
decoding times is linear in the interval between decoding times. For binary
symmetric channels, the RCSP approximation provides an efficiently-computed
approximation of performance that shows excellent agreement with a family of
rate-compatible, tail-biting convolutional codes in the short-latency regime.
For the additive white Gaussian noise channel, bounded-distance decoding
simplifies the computation of the marginal RCSP approximation and produces
similar results as analysis based on maximum-likelihood decoding for latencies
greater than 200. The efficiency of the marginal RCSP approximation facilitates
optimization of the lengths of incremental transmissions when the number of
incremental transmissions is constrained to be small or the length of the
incremental transmissions is constrained to be uniform after the first
transmission. Finally, an RCSP-based decoding error trajectory is introduced
that provides target error rates for the design of rate-compatible code
families for use in feedback communication systems.Comment: 23 pages, 15 figure
PPR: Partial Packet Recovery for Wireless Networks
Bit errors occur over wireless channels when the signal isn't strongenough to overcome the effects of interference and noise. Currentwireless protocols may use forward error correction (FEC) to correct forsome (small) number of bit errors, but generally retransmit the wholepacket if the FEC is insufficient. We observe that current wirelessmesh network protocols retransmit a number of packets and that most ofthese retransmissions end up sending bits that have already beenreceived multiple times, wasting network capacity. To overcome thisinefficiency, we develop, implement, and evaluate a partial packetrecovery (PPR) system.PPR incorporates three new ideas: (1) SoftPHY, an expandedphysical layer (PHY) interface to provide hints to the higher layersabout how ``close'' the actual received symbol was to the one decoded,(2) a postamble scheme to recover data even when a packet'spreamble is corrupted and not decodable at the receiver, and (3) PP-ARQ, an asynchronous link-layer retransmission protocol that allowsa receiver to compactly encode and request for retransmission only thoseportions of a packet that are likely in error.Our experimental results from a 27-node 802.15.4 testbed that includesTelos motes with 2.4 GHz Chipcon radios and GNU Radio nodes implementingthe Zigbee standard (802.15.4) show that PPR increases the framedelivery rate by a factor of 2x under moderate load, and7x under heavy load when many links have marginal quality
Joint Source-Channel Coding Optimized On End-to-End Distortion for Multimedia Source
In order to achieve high efficiency, multimedia source coding usually relies on the use of predictive coding. While more efficient, source coding based on predictive coding has been considered to be more sensitive to errors during communication. With the current volume and importance of multimedia communication, minimizing the overall distortion during communication over an error-prone channel is critical. In addition, for real-time scenarios, it is necessary to consider additional constraints such as fix and small delay for a given bit rate. To comply with these requirements, we seek an efficient joint source-channel coding scheme.
In this work, end-to-end distortion is studied for a first order autoregressive synthetic source that represents a general multimedia traffic. This study reveals that predictive coders achieve the same channel-induced distortion performance as memoryless codecs when applying optimal error concealment. We propose a joint source-channel system based on incremental redundancy that satisfies the fixed delay and error-prone channel constraints and combines DPCM as a source encoder and a rate-compatible punctured convolutional (RCPC) error control codec. To calculate the joint source-channel coding rate allocation that minimizes end-to-end distortion, we develop a Markov Decision Process (MDP) approach for delay constrained feedback Hybrid ARQ, and we use a Dynamic Programming (DP) technique. Our simulation results support the improvement in end-to-end distortion compared to a conventional Forward Error Control (FEC) approach with no feedback
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
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