DeepWiVe: deep-learning-aided wireless video transmission

We present DeepWiVe , the first-ever end-to-end joint source-channel coding (JSCC) video transmission scheme that leverages the power of deep neural networks (DNNs) to directly map video signals to channel symbols, combining video compression, channel coding, and modulation steps into a single neural transform. Our DNN decoder predicts residuals without distortion feedback, which improves the video quality by accounting for occlusion/disocclusion and camera movements. We simultaneously train different bandwidth allocation networks for the frames to allow variable bandwidth transmission. Then, we train a bandwidth allocation network using reinforcement learning (RL) that optimizes the allocation of limited available channel bandwidth among video frames to maximize the overall visual quality. Our results show that DeepWiVe can overcome the cliff-effect , which is prevalent in conventional separation-based digital communication schemes, and achieve graceful degradation with the mismatch between the estimated and actual channel qualities. DeepWiVe outperforms H.264 video compression followed by low-density parity check (LDPC) codes in all channel conditions by up to 0.0485 in terms of the multi-scale structural similarity index measure (MS-SSIM), and H.265+ LDPC by up to 0.0069 on average. We also illustrate the importance of optimizing bandwidth allocation in JSCC video transmission by showing that our optimal bandwidth allocation policy is superior to uniform allocation as well as a heuristic policy benchmark

Semantic and effective communications

Shannon and Weaver categorized communications into three levels of problems: the technical problem, which tries to answer the question "how accurately can the symbols of communication be transmitted?"; the semantic problem, which asks the question "how precisely do the transmitted symbols convey the desired meaning?"; the effectiveness problem, which strives to answer the question "how effectively does the received meaning affect conduct in the desired way?". Traditionally, communication technologies mainly addressed the technical problem, ignoring the semantics or the effectiveness problems. Recently, there has been increasing interest to address the higher level semantic and effectiveness problems, with proposals ranging from semantic to goal oriented communications. In this thesis, we propose to formulate the semantic problem as a joint source-channel coding (JSCC) problem and the effectiveness problem as a multi-agent partially observable Markov decision process (MA-POMDP). As such, for the semantic problem, we propose DeepWiVe, the first-ever end-to-end JSCC video transmission scheme that leverages the power of deep neural networks (DNNs) to directly map video signals to channel symbols, combining video compression, channel coding, and modulation steps into a single neural transform. We also further show that it is possible to use predefined constellation designs as well as secure the physical layer communication against eavesdroppers for deep learning (DL) driven JSCC schemes, making such schemes much more viable for deployment in the real world. For the effectiveness problem, we propose a novel formulation by considering multiple agents communicating over a noisy channel in order to achieve better coordination and cooperation in a multi-agent reinforcement learning (MARL) framework. Specifically, we consider a MA-POMDP, in which the agents, in addition to interacting with the environment, can also communicate with each other over a noisy communication channel. The noisy communication channel is considered explicitly as part of the dynamics of the environment, and the message each agent sends is part of the action that the agent can take. As a result, the agents learn not only to collaborate with each other but also to communicate "effectively'' over a noisy channel. Moreover, we show that this framework generalizes both the semantic and technical problems. In both instances, we show that the resultant communication scheme is superior to one where the communication is considered separately from the underlying semantic or goal of the problem.Open Acces

On Achieving Unconditionally Secure Communications Via the Physical Layer Approaches

Due to the broadcast nature, wireless links are open to malicious intrusions from outsiders, which makes the security issues a critical concern in the wireless communicationsover them. Physical-layer security techniques, which are based on the Shannon’s unconditional secrecy model, are effective in addressing the security issue while meeting the required performance level. According to the Wyner’s wiretap channel model, to achieve unconditionally security communication, the first step is to build up a wiretap channel with better channel quality between the legitimate communication peers than that of the eavesdropper; and the second step is to employ a robust security code to ensure that the legitimate users experience negligible errors while the eavesdropper is subject to 0.5 error probability. Motivated by this idea, in this thesis, we build wiretap channels for the single antenna systems without resorting to the spatial degree in commonly observed the multiple-input multiple-output (MIMO) systems. Firstly, to build effective wiretap channels, we design a novel scheme, called multi-round two-way communications (MRTWC). By taking feedback mechanisms into the design of Low Density Parity Check (LDPC) codes, our scheme adds randomness to the feedback signals from the destination to keep the eavesdropper ignorant while adding redundancy with the LDPC codes so that the legitimate receiver can correctly receive and decode the signals. Then, the channel BERs are specifically quantified according to the crossover probability in the case of Binary Symmetric Channel (BSC), or the Signal to Noise Ratio (SNR) in the case of AWGN and Rayleigh channels. Thus, the novel scheme can be utilized to address the security and reliability. Meanwhile, we develop a cross-layer approach to building the wiretap channel, which is suitable for high dynamic scenarios. By taking advantage of multiple parameters freedom in the discrete fractional Fourier transform (DFRFT) for single antenna systems, the proposed scheme introduces a distortion parameter instead of a general signal parameter for wireless networks based on DFRFT. The transmitter randomly flip-flops the uses of the distortion parameter and the general signal parameter to confuse the eavesdropper. An upper-layer cipher sequence will be employed to control the flip-flops. This cryptographic sequence in the higher layer is combined with the physical layer security scheme with random parameter fipping in DFRFT to guarantee security advantages over the main communication channel. As the efforts on the second step, this thesis introduces a novel approach to generate security codes, which can be used for encoding with low complexity by taking advantage of a matrix general inverse algorithm. The novel constructions of the security codes are based on binary and non-binary resilient functions. With the proposed security codes, we prove that our novel security codes can ensure 0.5 error probability seen by the wiretapper while close to zero by the intended receiver if the error probability of the wiretapper’s channel is over a derived threshold. Therefore, the unconditionally secure communication of legitimate partners can be guaranteed. It has been proved mathematically that the non-binary security codes could achieve closer to the security capacity bound than any other reported short-length security codes under BSC. Finally, we develop the framework of associating the wiretap channel building approach with the security codes. The advantages between legitimate partners are extended via developing the security codes on top of our cross-layer DFRFT and feedback MRTWC security communication model. In this way, the proposed system could ensure almost zero information obtained by the eavesdroppers while still keeping rather lower error transmissions for legitimate users. Extensive experiments are carried out to verify the proposed security schemes and demonstrate the feasibility and implement ability. An USRP testbed is also constructed, under which the physical layer security mechanisms are implemented and tested. Our study shows that our proposed security schemes can be implemented in practical communications settings

Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Towards 6G

The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of things (IoT), billions of sensors, machines, vehicles, drones, and robots will be connected, making the world around us smarter. The IoT will encompass devices that must wirelessly communicate a diverse set of data gathered from the environment for myriad new applications. The ultimate goal is to extract insights from this data and develop solutions that improve quality of life and generate new revenue. Providing large-scale, long-lasting, reliable, and near real-time connectivity is the major challenge in enabling a smart connected world. This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. Specifically, wireless technology enhancements for providing IoT access in fifth-generation (5G) and beyond cellular networks, and communication networks over the unlicensed spectrum are presented. Aligned with the main key performance indicators of 5G and beyond 5G networks, we investigate solutions and standards that enable energy efficiency, reliability, low latency, and scalability (connection density) of current and future IoT networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. Further, a vision of new paradigm shifts in communication networks in the 2030s is provided, and the integration of the associated new technologies like artificial intelligence, non-terrestrial networks, and new spectra is elaborated. Finally, future research directions toward beyond 5G IoT networks are pointed out.Comment: Submitted for review to IEEE CS&

Progressive transmission of medical images

A novel adaptive source-channel coding scheme for progressive transmission of medical images with a feedback system is therefore proposed in this dissertation. The overall design includes Discrete Wavelet Transform (DWT), Embedded Zerotree Wavelet (EZW) coding, Joint Source-Channel Coding (JSCC), prioritization of region of interest (RoI), variability of parity length based on feedback, and the corresponding hardware design utilising Simulink. The JSCC can achieve an efficient transmission by incorporating unequal error projection (UEP) and rate allocation. An algorithm is also developed to estimate the number of erroneous data in the receiver. The algorithm detects the address in which the number of symbols for each subblock is indicated, and reassigns an estimated correct data according to a decision making criterion, if error data is detected. The proposed system has been designed based on Simulink which can be used to generate netlist for portable devices. A new compression method called Compressive Sensing (CS) is also revisited in this work. CS exhibits many advantages in comparison with EZW based on our experimental results. DICOM JPEG2000 is an efficient coding standard for lossy or lossless multi-component image coding. However, it does not provide any mechanism for automatic RoI definition, and is more complex compared to our proposed scheme. The proposed system significantly reduces the transmission time, lowers computation cost, and maintains an error-free state in the RoI with regards to the above provided features. A MATLAB-based TCP/IP connection is established to demonstrate the efficacy of the proposed interactive and adaptive progressive transmission system. The proposed system is simulated for both binary and symmetric channel (BSC) and Rayleigh channel. The experimental results confirm the effectiveness of the design.EThOS - Electronic Theses Online ServiceGBUnited Kingdo