• Journal of KIISE:Information Networking
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• v.30 no.6
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• pp.755-763
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• 2003

To improve performance over noisy wireless channels, mobile wireless networks employ forward error correction(FEC) techniques. The performance of static FEC algorithms, however, degrades by poorly matching the overhead of their correction code to the degree of the fluctuating underlying channel error. This paper proposes an adaptive FEC technique called FECA(FEC-level Adaptation), which dynamically tunes FEC strength to the currently estimated channel error rate at the data link layer. FECA is suitable for wireless networks whose error rate is high and slowly changing compared to the round-trip time between two communicating nodes. One such example network would be a sensor network in which the average bit error rate is higher than $10^{-6}$ and the detected error rate at one time lasts a few hundred milliseconds on average. Our experiments show that FECA performs 15% in simulations with theoretically modeled wireless channels and in trace-driven simulations based on the data collected from real sensor networks better than any other static FEC algorithms.

• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.563-572
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• 2002

Wireless mobile networks tend to drop a large portion of packets due to propagation errors rather than congestion. To Improve reliability over noisy wireless channels, wireless networks can employ forward error correction (FEC) techniques. Static FEC algorithms, however, can degrade the performance by poorly matching their overhead to the degree of the underlying channel error, especially when the channel path loss rate fluctuates widely. This paper investigates the benefits of an adaptable FEC mechanism for wireless networks with severe packet loss by analytical analysis or measurements over a real wireless network called sensor network. We show that our adaptive FEC named FECA (FEC-level Adaptation) technique improves the performance by dynamically tuning FEC strength to the current amount of wireless channel loss. We quantify these benefits through a hybrid simulation integrating packet-level simulation with bit-level details and validate that FECA keeps selecting the appropriate FEC-level for a constantly changing wireless channel.

• Journal of Communications and Networks
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• v.13 no.2
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• pp.160-166
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• 2011

In u-healthcare services based on wireless body sensor networks, reliable connection is very important as many types of information, including vital signals, are transmitted through the networks. The transmit power requirements are very stringent in the case of in-body networks for implant communication. Furthermore, the wireless link in an in-body environment has a high degree of path loss (e.g., the path loss exponent is around 6.2 for deep tissue). Because of such inherently bad settings of the communication nodes, a multi-hop network topology is preferred in order to meet the transmit power requirements and to increase the battery lifetime of sensor nodes. This will ensure that the live body of a patient receiving the healthcare service has a reduced level of specific absorption ratio (SAR) when exposed to long-lasting radiation. We propose an efficientmethod for delivering delay-intolerant data packets over multiple hops. We consider forward error correction (FEC) in an erasure correction mode and develop a mathematical formulation for packet-level scheduling of delay-intolerant FEC packets over multiple hops. The proposed method can be used as a simple guideline for applications to setting up a topology for a medical body sensor network of each individual patient, which is connected to a remote server for u-healthcare service applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.62-77
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• 2010

Emerging applications with high data rates will need to transport bulk data reliably in wireless sensor networks. ARQ (Automatic Repeat request) or Forward Error Correction (FEC) code schemes can be used to provide reliable transmission in a sensor network. However, the naive ARQ approach drops the whole frame, even though there is a bit error in the frame and the FEC at the bit level scheme may require a highly complex method to adjust the amount of FEC redundancy. We propose a bulk data transmission scheme based on erasure-resilient code in this paper to overcome these inefficiencies. The sender fragments bulk data into many small blocks, encodes the blocks with LT codes and packages several such blocks into a frame. The receiver only drops the corrupted blocks (compared to the entire frame) and the original data can be reconstructed if sufficient error-free blocks are received. An incidental benefit is that the frame error rate (FER) becomes irrelevant to frame size (error recovery). A frame can therefore be sufficiently large to provide high utilization of the wireless channel bandwidth without sacrificing the effectiveness of error recovery. The scheme has been implemented as a new data link layer in TinyOS, and evaluated through experiments in a testbed of Zigbex motes. Results show single hop transmission throughput can be improved by at least 20% under typical wireless channel conditions. It also reduces the transmission time of a reasonable range of size files by more than 30%, compared to a frame ARQ scheme. The total number of bytes sent by all nodes in the multi-hop communication is reduced by more than 60% compared to the frame ARQ scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.5
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• pp.941-950
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• 2001

In this paper, we present the integrated network architecture for supporting mobile IP in third generation mobile communication networks, and propose the end-to-end QoS control mechanisms of DiffServ and QoS control functions of each network element in the proposed network. First, the QoS supporting schemes of IMT-2000 are described. Second, the necessities of integrating the networks are discussed and the integrated architecture are proposed. Third, the mapping between wireless channels and DiffServ classes are presented. Finally, the end-to-end QoS control mechanisms are proposed. We also analyze the link level protocols with QoS provisioning for mobile multimedia assuming that the system support voice and data traffic simultaneously. In case of data traffic, the delay and throughput of SREJ ARQ and Type-1 Hybrid ARQ scheme are compared, and In case of voice traffic, the packet loss rate of BCH coding is analyzed according to the varying data traffic loads. The results indicate that the adaptive link level protocols are efficient to meet the QoS requirements while the complexities are increased.

• Journal of KIISE:Information Networking
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• v.31 no.4
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• pp.375-383
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• 2004

As wireless mobile networks have been widely adopted due to their convenience for deployment, the research for improving their performance has been actively conducted. Since their throughput is restrained by the packet corruption rate not by congestion as in wired networks, however, network simulations for performance evaluation need to select the appropriate wireless channel model representing the behavior of propagation errors for the evaluated channel. The selection of the right model should depend on various factors such as the adopted frequency band, the level of signal power, the existence of obstacles against signal propagation, the sensitivity of protocols to bit errors, and etc. This paper analyzes 10-day bit traces collected from real sensor channels exhibiting the high bit error rate to determine a suitable sensor channel model. For selection, it also evaluates the performance of two error recovery algorithms such as a link layer FEC algorithm and three TCPs (Tahoe, Reno, and Vegas) over several channel models. The comparison analysis shows that CM(Chaotic Map) model predicts 3-time less BER variance and 10-time larger PER(Packet Error Rate) than traces while these differences between the other models and traces are larger than 10-time. The simulation experiments, furthermore, prove that CM model evaluates the performance of these algorithms over sensor channels with the precision at least 10-time more accurate than any other models.