The explosive growth of content-on-the-move, such as video streaming to mobile devices, has propelled research on multimedia broadcast and multicast schemes. Multirate transmission strategies have been proposed as a means of delivering layered services to users experiencing different downlink channel conditions. In this paper, we consider point-to-multipoint layered service delivery across a generic cellular system and improve it by applying different random linear network coding approaches. We derive packet error probability expressions and use them as performance metrics in the formulation of resource-allocation frameworks. The aim of these frameworks is both the optimization of the transmission scheme and the minimization of the number of broadcast packets on each downlink channel, while offering service guarantees to a predetermined fraction of users. As a case of study, our proposed frameworks are then adapted to the LTE-A standard and the eMBMS technology. We focus on the delivery of a video service based on the H.264 SVC standard and demonstrate the advantages of layered network coding over multirate transmission. Furthermore, we establish that the choice of both the network coding technique and the resource-allocation method play a critical role on the network footprint, as well as the quality of each received video layer.
With regards to the coding schemes that we will refer to, unlike @cite_19 and @cite_29 , this work focuses on NOW- and EW-RLNC schemes suitable for layered service transmissions. In addition, the authors of @cite_19 @cite_29 did not optimize the bit length of source packets used to represent the transmitted layered service; the source packet bit length is given a priori. This paper proposes a model for optimizing the source packet bit length to fit the transmission constraints of the communication standard in use. Since the bit length of source packets is constrained to be smaller than or equal to a maximum target value, the number of source packets representing a layered service can be upper-bounded. Hence, this work can represent the same layered service with a smaller number of source packets, compared to what proposed in @cite_29 . We remark that the number of source packets has a significant impact on the computation complexity of the RLNC decoding phase @cite_25 .
@cite_19 @cite_29 @cite_25
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In an unreliable single-hop broadcast network setting, we investigate the throughput and decoding-delay performance of random linear network coding as a function of the coding window size and the network size. Our model consists of a source transmitting packets of a single flow to a set of @math users over independent erasure channels. The source performs random linear network coding (RLNC) over @math (coding window size) packets and broadcasts them to the users. We note that the broadcast throughput of RLNC must vanish with increasing @math , for any fixed @math Hence, in contrast to other works in the literature, we investigate how the coding window size @math must scale for increasing @math . Our analysis reveals that the coding window size of @math represents a phase transition rate, below which the throughput converges to zero, and above which it converges to the broadcast capacity. Further, we characterize the asymptotic distribution of decoding delay and provide approximate expressions for the mean and variance of decoding delay for the scaling regime of @math These asymptotic expressions reveal the impact of channel correlations on the throughput and delay performance of RLNC. We also show how our analysis can be extended to other rateless block coding schemes such as the LT codes. Finally, we comment on the extension of our results to the cases of dependent channels across users and asymmetric channel model. We investigate the performance of delay constrained data transmission over wireless networks without end-to-end feedback. Forward error-correction coding (FEC) is performed at the bit level to combat channel distortions and random linear network coding (RLNC) is performed at the packet level to recover from packet erasures. We focus on the scenario where RLNC re-encoding is performed at intermediate nodes and we assume that any packet that contains bit errors after FEC decoding can be detected and erased. To facilitate explicit characterization of data transmission over network-coded wireless systems, we propose a generic two-layer abstraction of a network that models both bit symbol-level operations at the lower layer (termed PHY-layer) over several heterogeneous links and packet-level operations at the upper layer (termed NET-layer). Based on this model, we propose a network reduction method to characterize the throughput-reliability function of the end-to-end transmission. Our approach not only reveals an explicit tradeoff between data delivery rate and reliability, but also provides an intuitive visualization of the bottlenecks within the underlying network. We illustrate our approach via a point-to-point link and a relay network and highlight the advantages of this method over capacity-based approaches. In an unreliable single-hop broadcast network setting, we investigate the throughput and decoding-delay performance of random linear network coding as a function of the coding window size and the network size. Our model consists of a source transmitting packets of a single flow to a set of n users over independent time-correlated erasure channels. The source performs random linear network coding (RLNC) over k (coding window size) packets and broadcasts them to the users. We note that the broadcast throughput of RLNC must vanish with increasing n, for any fixed k. Hence, in contrast to other works in the literature, we investigate how the coding window size k must scale for increasing n. Our analysis reveals that the coding window size of Θ(ln(n)) represents a phase transition rate, below which the throughput converges to zero, and above which, it converges to the broadcast capacity. Further, we characterize the asymptotic distribution of decoding delay and provide approximate expressions for the mean and variance of decoding delay for the scaling regime of k=ω(ln(n)). These asymptotic expressions reveal the impact of channel correlations on the throughput and delay performance of RLNC. We also show that how our analysis can be extended to other rateless block coding schemes such as the LT codes. Finally, we comment on the extension of our results to the cases of dependent channels across users and asymmetric channel model. Layered video coding is capable of progressively refining the reconstructed video quality with the aid of multiple layers of unequal importance. When the base layer (BL) is corrupted or lost due to channel impairments, the enhancement layers (ELs) must be discarded by the video decoder, regardless whether they are perfectly decoded or not, which implies that the transmission power assigned to the ELs is wasted. To circumvent this problem, we proposed a bit-level inter-layer forward error correction (IL-FEC) scheme for layered video transmission in our previous work, which implanted the systematic bits of the BL into the systematic bits of the ELs using exclusive-OR operations (XOR). This allowed the receiver to exploit the implanted bits of the ELs for assisting the BL's decoding and hence improved the overall system performance of our IL-FEC aided layered video scheme. In this treatise, we find the specific FEC coding rates in a real-time on-line fashion for the sake optimizing the overall system performance. The proposed procedure is widely applicable to diverse wireless transceivers and FEC codecs. Our simulation results show that the proposed optimized IL-FEC system outperforms the traditional optimal UEP by about 1.9 dB of Eb N0 at a peak signal-to-noise ratio (PSNR) of 38 dB. Viewing the improvements in terms of the video quality, 3.3 dB of PSNR improvement is attained at an Eb N0 of 10 dB, when employing a recursive systematic convolutional (RSC) code.