Review of Rateless-Network-Coding-Based Packet Protection in Wireless Sensor Networks

Abdullah, Ahmad S.; Abbasi, Mohammad Javad; Fisal, Norsheila

doi:10.1155/2015/641027

Cited by 5 publications

(6 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The basic concept of rateless codes is illustrated in Figure 1 [1]. From the figure, a total of k c packets, obtained from the fragmented source data, are encoded by the transmitter to get a large number of encoded packets n c .…”

Section: Concept Of Rateless Codesmentioning

confidence: 99%

“…To illustrate the importance of rateless codes, let's assume that we have a fixed-rate code C fixed of fixed-code rate R fixed designed to achieve a performance close to the channel capacity target C target at a specific signal-to-noise-ratio (SNR), ϕ fixed . However, the channel fluctuations make the fixed-rate code impose two limitations [1]. First, if the actual SNR at the receiver is actually greater than ϕ fixed , then the code essentially becomes an inefficient channel code.…”

Section: Concept Of Rateless Codesmentioning

confidence: 99%

“…In practice, the transmitted data over the channel are usually affected by noise, interference, and fading. Several channel models, such as additive white Gaussian noise (AWGN), binary symmetrical channel (BSC), binary erasure channel (BECH), wireless fading channel, and lossy (or erasure) channel, are introduced in which errors' (or losses) control technique is required to reduce the errors (or losses) caused by such channel impairments [1].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Rateless Space-Time Block Codes for 5G Wireless Communication Systems

Alqahtani¹

2019

The Fifth Generation (5G) of Wireless Communication

View full text Add to dashboard Cite

This chapter presents a rateless space-time block code (RSTBC) for massive multiple-input multiple-output (MIMO) wireless communication systems. We discuss the principles of rateless coding compared to the fixed-rate channel codes. A literature review of rateless codes (RCs) is also addressed. Furthermore, the chapter illustrates the basis of RSTBC deployments in massive MIMO transmissions over lossy wireless channels. In such channels, data may be lost or are not decodable at the receiver end due to a variety of factors such as channel losses or pilot contamination. Massive MIMO is a breakthrough wireless transmission technique proposed for future wireless standards due to its spectrum and energy efficiencies. We show that RSTBC guarantees the reliability of the system in such highly lossy channels. Moreover, pilot contamination (PC) constitutes a particularly significant impairment in reciprocity-based multi-cell systems. PC results from the non-orthogonality of the pilot sequences in different cells. In this chapter, RSTBC is also employed in the downlink transmission of a multi-cell massive MIMO system to mitigate the effects of signal-to-interference-and-noise ratio (SINR) degradation resulting from PC. We conclude that RSTBC can effectively mitigate such interference. Hence, RSTBC is a strong candidate for the upcoming 5G wireless communication systems.

show abstract

Section: Concept Of Rateless Codesmentioning

confidence: 99%

Section: Concept Of Rateless Codesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Rateless Space-Time Block Codes for 5G Wireless Communication Systems

Alqahtani¹

2019

The Fifth Generation (5G) of Wireless Communication

View full text Add to dashboard Cite

show abstract

“…Luby transform (LT) codes, which were proposed by Luby in 2002, were the first practical RC [8]. The basic idea of LT codes is that the sender limitlessly and randomly sends encoded symbols until the receiver can successfully recover the symbol information of the source end [9]. Data gathering via LT codes can achieve high reliability.…”

Section: Introductionmentioning

confidence: 99%

Reliable and Energy-Efficient Data Gathering in Wireless Sensor Networks via Rateless Codes and Compressed Sensing

Song¹

2018

IJPE

View full text Add to dashboard Cite

It is difficult for data gathering via a fixed code rate in wireless sensor networks (WSNs) to achieve reliable recovery. Compared with the fixed code rate, rateless codes can continuously send a code word to the sink node until the source node information is recovered. Thus, data gathering methods based on rateless codes are effective in achieving reliable data in the sink node. However, to achieve high reliability, a large amount of sensor data must be collected, and this greatly increases the energy consumption of sensor nodes and the storage space of the sink nodes. Fortunately, data gathering via compressed sensing (CS) can largely reduce the number of sensor data collected to further save energy consumption and storage space. This paper proposes a data gathering method via rateless codes and CS. The proposed method can not only achieve reliable recovery, but also save energy consumption of data collection and storage space of the sink nodes. The experimental results show that the proposed method can reduce energy consumption by about 40% and storage space by about 40% compared with the data gathering via LT codes, which are a typical rateless code.

show abstract

“…Upon successful reception of the interest messages, each sensor node floods the sensed information to its neighbours. Associated with routing concept is the idea of a network coding technique in which relay nodes combine packets using mathematical (numerical or logical) operations such that the number of transmitted packets is significantly reduced [3]. Network coding has been extensively applied in wired networks' applications to increase throughput.…”

Section: Introductionmentioning

confidence: 99%

Cooperative and Adaptive Network Coding for Gradient Based Routing in Wireless Sensor Networks with Multiple Sinks

Migabo

Olwal

Djouani

et al. 2017

Journal of Computer Networks and Communications

View full text Add to dashboard Cite

Despite its low computational cost, the Gradient Based Routing (GBR) broadcast of interest messages in Wireless Sensor Networks (WSNs) causes significant packets duplications and unnecessary packets transmissions. This results in energy wastage, traffic load imbalance, high network traffic, and low throughput. Thanks to the emergence of fast and powerful processors, the development of efficient network coding strategies is expected to enable efficient packets aggregations and reduce packets retransmissions. For multiple sinks WSNs, the challenge consists of efficiently selecting a suitable network coding scheme. This article proposes a Cooperative and Adaptive Network Coding for GBR (CoAdNC-GBR) technique which considers the network density as dynamically defined by the average number of neighbouring nodes, to efficiently aggregate interest messages. The aggregation is performed by means of linear combinations of random coefficients of a finite Galois Field of variable size GF(2 ) at each node and the decoding is performed by means of Gaussian elimination. The obtained results reveal that, by exploiting the cooperation of the multiple sinks, the CoAdNC-GBR not only improves the transmission reliability of links and lowers the number of transmissions and the propagation latency, but also enhances the energy efficiency of the network when compared to the GBR-network coding (GBR-NC) techniques.

show abstract

Review of Rateless-Network-Coding-Based Packet Protection in Wireless Sensor Networks

Cited by 5 publications

References 42 publications

Rateless Space-Time Block Codes for 5G Wireless Communication Systems

Rateless Space-Time Block Codes for 5G Wireless Communication Systems

Reliable and Energy-Efficient Data Gathering in Wireless Sensor Networks via Rateless Codes and Compressed Sensing

Cooperative and Adaptive Network Coding for Gradient Based Routing in Wireless Sensor Networks with Multiple Sinks

Contact Info

Product

Resources

About