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Application Layer Forward Error Correction for Mobile Multimedia Broadcasting
Published in Borko Furht, Syed Ahson, Handbook of Mobile Broadcasting, 2008
Thomas Stockhammer, Amin Shokrollahi, Mark Watson, Michael Luby, Tiago Gasiba
Fountain codes are a novel and innovative class of codes designed for transmission of data over time varying and unknown erasure channels. They were first mentioned without an explicit construction in [13], and the first efficient construction was invented by Luby [14]. A fountain code designed for k source symbols is specified by a probability distribution D on the set of binary strings of length k. Operationally, a fountain code can produce from the vector x a potentially limitless stream of symbols y1, y2, y3, …, called output symbols, satisfying several fundamental properties: Each output symbol can be generated according to the following probabilistic process: the distribution D is sampled to yield a vector (a1, …, ak), and the value of the output symbol is set to be ⊕i=1kaixi. This process is referred to as encoding, and the vector (a1, …, ak) is called the mask corresponding to the output symbol.The output symbols can be independently generated.The source symbols can be recovered from any set of n output symbols, with high probability. The recovery process is usually called decoding, and the number n / k − 1 is called the overhead of the decoder. The probability that the decoder fails is called the error probability of the code.
Performance statistics of broadcasting networks with receiver diversity and Fountain codes
Published in Journal of Information and Telecommunication, 2023
Lam-Thanh Tu, Tan N. Nguyen, Phuong T. Tran, Tran Trung Duy, Quang-Sang Nguyen
Improving spectral efficiency (SE) and/or energy efficiency (EE) in the contemporary ultra-dense wireless networks such as, cellular networks (Di Renzo et al., 2018; Di Renzo, Zappone, et al., 2019; Hossain, 2022), low power wide area networks (LPWAN) with LoRa (Nguyen et al., 2020; Tu et al., 2021; Tu, Bradai, et al., 2022), SigFox, and WiFi networks (Feng et al., 2022; Ragpot et al., 2019), is a challenging task owing to the strong interference. There are many approaches in the literature, for example, relaying networks (Nguyen and Kong, 2017; Pham et al., 2022), energy harvesting (Nguyen and Kong, 2016; N. T. Nguyen et al., 2019), full-duplex communications, satellite communications (N. T. Nguyen et al., in press) and unmanned aerial devices (UAV) (Motlagh et al., 2021), are proposed to figure out this problem. Nevertheless, these techniques fairly boost up the SE and the EE since it only focuses on point-to-point communications rather than considering either multi-cast or broadcast networks. Broadcasting networks, differently, simultaneously broadcast information to all users instead of transmitting consecutively to all users. As a consequence, ones can theoretically facilitate the SE and the EE of the networks. Nevertheless, it is an extremely difficult task, in reality, to successfully broadcast messages to all users under limited resources (frequency and/or time). The principal reason is that each user suffers from different fading levels and different transmission distances. Consequently, there is a high probability that some users are not able to decode the error-free message. The sender, as a result, needs to re-send these lost packets until all users successfully receive those messages (Hassan et al., 2019). The situation gets worse if the number of devices goes without bound. Thus, the broadcasting networks is not attracted many researchers unless the re-transmission problem is figured out. Fortunately, a powerful coding scheme namely Fountain code has been proposed recently which can overcome such issue (Indoonundon & Fowdur, 2021). In fact, with Fountain code, the message is divided into many equal-length packets and each packet is encoded by a random generator matrix which ensures that each novel packet is independent of the previous one. On the receiver side, it only requires to collect a sufficient number of packets to decode the message and is uncorrelated with other users. As a result, it overcomes the re-transmission issue. Nevertheless, in the 5G-Advanced era, employing broadcasting networks is insufficient to ensure reliability owing to the strong interference. Therefore, other techniques which significantly facilitate the system diversity are required along with the broadcasting networks to achieve a comprehensive performance. One of the outstanding technologies to boost reliability is to employ the receiver diversity techniques such as maximal ratio combining (MRC) and selection combining (SC) (Tu et al., 2018). Under this context, in the present paper, we investigate the performance of the broadcasting networks utilizing Fountain code and receiver diversity techniques.