Suffering from serious rate degradation, how to improve transmission rate with low latency is a challenging issue in ultra-reliable and low-latency communications (URLLC), especially when there is no enough blocklength for data transmission. To handle this issue, we propose to integrate the reconfigurable intelligent surface (RIS) and superimposed pilot (SP) into massive multiple-input multiple-output (mMIMO) systems, where the SP ensures latency by simultaneously sending pilot and data while the RIS improves high transmission rate by reflecting the SP signals. Practically, we derive the finite blocklength ergodic achievable rate lower bound in closed form under imperfect channel estimation and pilot interference removal. Then, we maximize the weighted sum rate of all the users by jointly designing the power control of SP at each user and the phase shifts at the RIS. Due to the highly coupled variables, we first decompose the original problem into the phase shift design subproblem and the power control design subproblem, which are resolved by a genetic algorithm (GA) and an iterative algorithm based on geometric programming (GP). Then, a block coordinate descent algorithm is proposed. Correspondingly, the complexity and convergence of the proposed algorithms are analyzed. Finally, our numerical results demonstrate that the joint design scheme can bring effective rate improvement in stringent latency constraints.

Ultra-reliable and low-latency communication (URLLC) is recognized as the most challenging use case for the next generation of wireless networks. Existing research on URLLC is based on the regular pilot (RP) scheme, which is tough to ensure a high transmission rate with stringent latency and reliability requirements due to the impact of finite blocklength, especially in massive connectivity scenarios. In this paper, we propose to use generalized superimposed pilot (GSP) scheme for URLLC transmission in massive multi-input multi-output (mMIMO) systems. Distinguishing from the conventional superimposed pilot (SP) scheme, the GSP scheme eliminates mutual interference between the pilot and data, where the data length is optimized, and the data symbols are precoded to spread over the whole transmission block. With the GSP scheme, we first formulate a weighted sum rate maximization problem by jointly optimizing the data length, pilot power, and data power and then derive closed-form results, including suboptimal data length and achievable rate lower bounds with maximum-ratio combining (MRC) and zero-forcing (ZF) detectors, respectively. Based on the closed-form results, we provide the corresponding iterative algorithms for the MRC and ZF cases where the problems are transformed into geometry program format by using log-function and successive convex approximation methods. Finally, the performance of the RP, SP, and GSP schemes are compared through simulation results, which reflect the superiority and robustness of the GSP scheme in URLLC scenarios.

Driven by the development of time-sensitive applications, short packet transmission (SPT) design has become the key point in the ultra-reliable and low-latency communications (URLLC) area. The primary challenge in it is that the delay caused by pilot overhead cannot be neglected. To deal with this issue, this paper presents a frame structure adopting partial-superimposed-pilot (PSP) scheme for SPT. The key of PSP scheme is that the number of data symbols is equal to the available blocklength, and the number of pilot symbols transmitted with data in the training stage needs to be optimized. Under the finite blocklength regime, we first derive a closed-form lower bound achievable rate of an uplink massive MIMO system with imperfect pilot removal for maximal-ratio-combining (MRC) receiver. Then, we formulate a weighted sum rate maximization problem by jointly optimizing the pilot length, pilot power, and data power. We derive a closed-form solution of optimal pilot length. Using the log-function and successive convex approximation (SCA) method, we develop an iterative optimization framework to find a locally optimal power solution. For comparison, the conventional frame structures based on complete-superimposed-pilot (CSP) and regular pilot (RP) schemes are also shown. Simulation results indicate that the proposed PSP scheme is superior to the existing CSP and RP schemes.

With the fast proliferation of online video sites and social media platforms, user, professionally and occupationally generated content (UGC, PGC, OGC) videos are streamed and explosively shared over the Internet. Consequently, it is urgent to monitor the content quality of these Internet videos to guarantee the user experience. However, most existing modern video quality assessment (VQA) databases only include UGC videos and cannot meet the demands for other kinds of Internet videos with real-world distortions. To this end, we collect 1,072 videos from Youku, a leading Chinese video hosting service platform, to establish the Internet video quality assessment database (Youku-V1K). A special sampling method based on several quality indicators is adopted to maximize the content and distortion diversities within a limited database, and a probabilistic graphical model is applied to recover reliable labels from noisy crowdsourcing annotations. Based on the properties of Internet videos originated from Youku, we propose a spatio-temporal distortion-aware model (STDAM). First, the model works blindly which means the pristine video is unnecessary. Second, the model is familiar with diverse contents by pre-training on the large-scale image quality assessment databases. Third, to measure spatial and temporal distortions, we introduce the graph convolution and attention module to extract and enhance the features of the input video. Besides, we leverage the motion information and integrate the frame-level features into video-level features via a bi-directional long short-term memory network. Experimental results on the self-built database and the public VQA databases demonstrate that our model outperforms the state-of-the-art methods and exhibits promising generalization ability.

The application of cloud storage system has been deployed widely in recent years. A lot of electronic medical records (EMRs) are collected and uploaded to the cloud for scalable sharing among the authority users. It is necessary to guarantee the confidentiality of EMRs and the privacy of EMR owners. To achieve this target, we summarize a series of attack behaviors in the cloud storage system and present the security model against many types of unexpected privacy leakage. Privacy of unassailed EMRs is guaranteed in this model, and the influence of privacy leakage is controlled in a certain scope. We also propose a role-based access control scheme to achieve flexible access control on these private EMRs. One can access medical records only if his/her role satisfies the defined access policy, which implies a fine-grained access control. Theoretical and experimental analyses show the efficiency of our scheme in terms of computation and communication.

Electronic Health Record (EHR) system facilitates us a lot for health record management. Privacy risk of patients' records is the dominating obstacle in the widely deployed EHRs. Role-based access control (RBAC) schemes offer an access control on EHRs according to one's role. Only the medical staff with roles satisfying the specified access policies can read EHRs. In existing schemes, attackers can link patients' identities to their doctors. Therefore, the classification of patients' diseases are leaked without actually knowing patients' EHRs. To address this problem, we present an anonymous RBAC scheme. Not only it achieves flexible access control, but also realizes privacy-preserving for individuals. Moreover, our scheme maintains the property of constant size for the encapsulated EHRs. The proposed security models with semantic security and anonymity can be proven under decisional bilinear group assumptions. Besides, we provide an approach for EHR owners to search out their targeted EHR in the anonymous system. For better user experience, we apply "online/offline" approach to speed up data processing in our scheme. Experimental results show that the time consumption for key generation and EHR encapsulation can be done in milliseconds.