This paper presents a promising design concept for reconfigurable intelligent surfaces (RISs), named plug-in RIS, wherein the RIS is plugged into an appropriate position in the environment, adjusted once according to the location of both base station and blocked region, and operates with fixed beams to enhance the system performance. The plug-in RIS is a novel system design, streamlining RIS-assisted millimeter-wave (mmWave) communication without requiring decoupling two parts of the end-to-end channel, traditional control signal transmission, and online RIS configuration. In plug-in RIS-aided transmission, the transmitter efficiently activates specific regions of the divided large RIS by employing hybrid beamforming techniques, each with predetermined phase adjustments tailored to reflect signals to desired user locations. This user-centric approach enhances connectivity and overall user experience by dynamically illuminating the targeted user based on location. By introducing plug-in RIS’s theoretical framework, design principles, and performance evaluation, we demonstrate its potential to revolutionize mmWave communications for the limited channel state information (CSI) scenarios. Simulation results illustrate that plug-in RIS provides power/cost-efficient solutions to overcome blockage in the mmWave communication system and a striking convergence in average bit error rate and achievable rate performance with traditional full CSI-enabled RIS solutions.

Utilizing the abundant bandwidth in millimeter wave frequency bands is an interesting option to enable wireless communication services with challenging latency and reliability requirements for factory automation. Nevertheless, millimeter wave bands have less favorable propagation properties compared to lower bands, which impacts the coverage negatively. In this paper, we show that millimeter wave bands can fulfill extreme latency and reliability requirements with much higher system capacity than mid-band frequencies by means of beamforming, large antenna arrays, and network densification. This makes millimeter wave bands suitable for providing ultra-reliable low-latency communication services for factory automation. However, we find that small beam misalignments due to channel state information error can degrade the system capacity substantially.

We study the repair problem in distributed storage systems where storage nodes are connected through packet erasure channels and some nodes are dedicated to repair [termed as dedicated-for-repair (DR) storage nodes]. We first investigate the minimum required repair-bandwidth in an asymptotic setup, in which the stored file is assumed to have an infinite size. The result shows that the asymptotic repair-bandwidth over packet erasure channels with a fixed erasure probability has a closed-form relation to the repair-bandwidth in lossless networks. Next, we show the benefits of DR storage nodes in reducing the repair bandwidth, and then we derive the necessary minimal storage space of DR storage nodes. Finally, we study the repair in a nonasymptotic setup, where the stored file size is finite. We study the minimum practical-repair-bandwidth, i.e., the repair-bandwidth for achieving a given probability of successful repair. A combinatorial optimization problem is formulated to provide the optimal practical-repair-bandwidth for a given packet erasure probability. We show the gain of our proposed approaches in reducing the repair-bandwidth.

The problem of exact repair of a failed node in multi-hop networked distributed storage systems is considered. Contrary to the most of the current studies which model the repair process by the direct links from surviving nodes to the new node, the repair is modeled by considering the multi-hop network structure, and taking into account that there might not exist direct links from all the surviving nodes to the new node. In the repair problem of these systems, surviving nodes may cooperate to transmit the repair traffic to the new node. In this setting, we define the total number of packets transmitted between nodes as repair-cost. A lower bound of the repair-cost can thus be found by cut-set bound analysis. In this paper, we show that the lower bound of the repair-cost is achievable for the exact repair of MDS codes in tandem and grid networks, thus resulting in the minimum-cost exact MDS codes. Further, two suboptimal (achievable) bounds for the large scale grid networks are proposed.

We study the repair problem of distributed storage systems in erasure networks where the packets transmitted from surviving nodes to the new node might be lost. The fundamental storage-bandwidth tradeoff is calculated by multicasting analysis in erasure networks. The optimal tradeoff bound can be asymptotically achieved when the number of transmission (packets) goes to infinity. For a limited number of transmission, we study the probability of successful regenerating. Then, we investigate two approaches of increasing the probability of successful regenerating, namely, by connecting more surviving nodes or by increasing the storage space of nodes. Using more nodes may pose larger delay and in certain situation it might not be possible to connect to more nodes too. We show that in addition to reducing repair bandwidth, increasing storage space can also increase reliability for repair.

There have been emerging lots of applications for distributed storage systems e.g., those in wireless sensor networks or cloud storage. Since storage nodes in wireless sensor networks have limited battery, it is valuable to find a repair scheme with optimal transmission costs (e.g., energy). The optimal-cost repair has been recently investigated in a centralized way. However a centralized control mechanism may not be available or is very expensive. For the scenarios, it is interesting to study optimal-cost repair in a decentralized setup. We formulate the optimal-cost repair as convex optimization problems for the network with convex transmission costs. Then we use primal and dual decomposition approaches to decouple the problem into subproblems to be solved locally. Thus, each surviving node, collaborating with other nodes, can minimize its transmission cost such that the global cost is minimized. We further study the optimality and convergence of the algorithms. Finally, we discuss the code construction and determine the field size for finding feasible network codes in our approaches.

In distributed storage systems reliability is achieved through redundant storage nodes distributed in the network. Then a data collector can recover source information even if some nodes fail. To maintain reliability, an autonomous and efficient protocol should be used to reconstruct the failed node. The repair process causes traffic in the network. Recent results in e.g., [1], [2] found the optimal traffic-storage tradeoff, and proposed regenerating codes to achieve the optimality. We investigate the link costs and the impact of network topologies during the repair process. We formulate the minimum cost repair problem in joint and decoupled methods. We investigate the required field size for the joint method. For the decoupled method, we show that the optimization problem is linear for the linear cost. We further show that the cooperation of surviving nodes could efficiently exploit the network topology and reduce the repair cost. The numerical results in tandem, star and grid networks show the benefits of our methods in term of the repair cost.