The transmission of JPEG2000 images over wireless channels is examined using reorganization of the compressed images into error-resilient, product-coded streams. The product-code consists of Turbo-codes and Reed-Solomon codes which are optimized using an iterative process. The generation of the stream to be transmitted is performed directly using compressed JPEG2000 streams. The resulting scheme is tested for the transmission of compressed JPEG2000 images over wireless channels and is shown to outperform other algorithms which were recently proposed for the wireless transmission of images.

This paper studies the affine frequency division multiplexing (AFDM)-empowered sparse code multiple access (SCMA) system, referred to as AFDM-SCMA, for supporting massive connectivity in high-mobility environments. First, by placing the sparse codewords on the AFDM chirp subcarriers, the input-output (I/O) relation of AFDM-SCMA systems is presented. Next, we delve into the generalized receiver design, chirp rate selection, and error rate performance of the proposed AFDM-SCMA The proposed AFDM-SCMA is shown to provide a general framework and subsume the existing OFDM-SCMA as a special case. Third, for efficient transceiver design, we further propose a class of sparse codebooks for simplifying the I/O relation, referred to as I/O relation-inspired codebook design in this paper. Building upon these codebooks, we propose a novel iterative detection and decoding scheme with linear minimum mean square error (LMMSE) estimator for both downlink and uplink channels based on orthogonal approximate message passing principles. Our numerical results demonstrate the superiority of the proposed AFDM-SCMA systems over OFDM-SCMA systems in terms of the error rate performance. We show that the proposed receiver can significantly enhance the error rate performance while reducing the detection complexity.

A novel image transmission scheme is proposed for the communication of set partitioning in hierarchical trees image streams over wireless channels. The proposed scheme employs turbo codes and Reed-Solomon codes in order to deal effectively with burst errors. An algorithm for the optimal unequal error protection of the compressed bitstream is also proposed and applied in conjunction with an inherently more efficient technique for product code decoding. The resulting scheme is tested for the transmission of images over wireless channels. Experimental evaluation clearly demonstrates the superiority of the proposed transmission system in comparison to well-known robust coding schemes.

We address the problem of prioritized video streaming over lossy overlay networks. We propose to exploit network path diversity via a novel randomized network coding (RNC) approach that provides unequal error protection (UEP) to the packets conveying the video content. We design a distributed receiver-driven streaming solution, where a client requests packets from the different priority classes from its neighbors in the overlay. Based on the received requests, a node in turn forwards combinations of the selected packets to the requesting peers. Choosing a network coding strategy at every node can be cast as an optimization problem that determines the rate allocation between the different packet classes such that the average distortion at the requesting peer is minimized. As the optimization problem has log-concavity properties, it can be solved with low complexity by an iterative algorithm. Our simulation results demonstrate that the proposed scheme respects the relative priorities of the different packet classes and achieves a graceful quality adaptation to network resource constraints. Therefore, our scheme substantially outperforms reference schemes such as baseline network coding techniques as well as solutions that employ rateless codes with built-in UEP properties. The performance evaluation provides additional evidence of the substantial robustness of the proposed scheme in a variety of transmission scenarios.

360° video is becoming an increasingly popular technology on commercial social platforms and vital part of emerging Virtual Reality/Augmented Reality (VR/AR) applications. However, the delivery of 360° video content in mobile networks is challenging because of its size. The encoding of 360° video into multiple quality layers and tiles and edge cache-assisted video delivery have been proposed as a remedy to the excess bandwidth requirements of 360° video delivery systems. Existing works using the above tools have shown promising performance for Video-on-Demand (VoD) 360° delivery, but they cannot be straightforwardly extended in a live-streaming setup. Motivated by the above, we study edge cache-assisted 360° live video streaming to increase the overall quality of the delivered 360° videos to users and reduce the service cost. We employ Long Short-Term Memory (LSTM) networks to forecast the evolution of the content requests and prefetch content to caches. To further enhance the delivered video quality, users located in the overlap of the coverage areas of multiple Small Base Stations (SBSs) are allowed to receive data from any of these SBSs. We evaluate and compare the performance of our algorithm with Least Frequently Used (LFU), Least Recently Used (LRU), and First In First Out (FIFO) algorithms. The results show the superiority of the proposed approach in terms of delivered video quality, cache-hit-ratio and backhaul link usage.

360°video is an essential component of VR/AR/MR systems that provides immersive experience to the users. However, 360° video is associated with high bandwidth requirements. The required bandwidth can be reduced by exploiting the fact that users are interested in viewing only a part of the video scene and that users request viewports that overlap with each other. Motivated by the findings of our recent works where the benefits of caching video tiles at edge servers instead of caching entire 360° videos were shown, in this paper, we introduce the concept of virtual viewports that have the same number of tiles with the original viewports. The tiles forming these viewports are the most popular ones for each video and are determined by the users' requests. Then, we propose a proactive caching scheme that assumes unknown videos' and viewports' popularity. Our scheme determines which videos to cache as well as which is the optimal virtual viewport per video. Virtual viewports permit to lower the dimensionality of the cache optimization problem. To solve the problem, we first formulate the content placement of 360° videos in edge cache networks as a Markov Decision Process (MDP), and then we determine the optimal caching placement using the Deep Q-Network (DQN) algorithm. The proposed solution aims at maximizing the overall quality of the 360° videos delivered to the end-users by caching the most popular 360° videos at base quality along with a virtual viewport in high quality. We extensively evaluate the performance of the proposed system and compare it with that of known systems such as Least Frequently Used (LFU), Least Recently Used (LRU), First-In-First-Out (FIFO), over both synthetic and real 360° video traces. The results reveal the large benefits coming from proactive caching of virtual viewports instead of the original ones in terms of the overall quality of the rendered viewports, the cache hit ratio, and the servicing cost.