Sriharsha Magani

Bio: Sriharsha Magani is an academic researcher from Indian Institute of Technology, Hyderabad. The author has contributed to research in topics: Synchronization & Frame (networking). The author has an hindex of 1, co-authored 1 publications receiving 2 citations.

Cell-search and tracking of residual time and frequency offsets in low power NB-IoT devices

Abstract: Initial synchronization and cell-search in cellular based systems is the first step of establishing communication link between user equipment (UE) and base station (BS). Under this process UE aligns to the timing and frequency of the BS and acquires critical information like cell-ID, frame number and system bandwidth. Narrow band IoT (NB-IoT) is 3GPP defined cellular based IoT technology in which cell-search is facilitated through a set of two signals namely NB primary synchronization signal (NPSS) and NB secondary synchronization signal (NSSS). Across all BS, the same NPSS sequence is used. However, the NSSS sequences is used to distinguish them using a cell identity. We assume NPSS based initial synchronization is carried out to estimate timing and frequency offsets using existing traditional algorithms. In this paper, we first propose NSSS detection algorithm which is used to detect cell-ID and partial information of frame numbering. Post initial cell-search, UE has to be constantly synchronized to the BS in order to transmit or receive the data. For this purpose of periodic tracking of the timing and frequency offsets we make use of NB reference signals (NRSs). In the second part of the paper, we present an algorithm to track the residual time and frequency offsets using NRS which are distributed across frequency and time grid. We show novel algorithms that achieve significant detection performance even at low SNR values like − 12 dB which is the typical operating range for low power NB-IoT devices. The simulation results prove these claims.

Complexity-Effective Sequential Detection of Synchronization Signal for Cellular Narrowband IoT Communication Systems

Abstract: Narrowband Internet of Things (NB-IoT) is one of the most promising low-power wide-area technologies to support low cost, massive connection, deep coverage, and low-power consumption. This article proposes a complexity-effective narrowband secondary synchronization signal (NSSS) detection scheme for the cellular NB-IoT communication system. By taking advantage of the NSSS sequence, the search space of NSSS hypotheses is reduced by decoupling the detection of complementary Walsh sequence and Zadoff–Chu sequence in a sequential manner. Such a detection strategy allows reduced-complexity NSSS detection in the NB-IoT system. Both numerical and simulation results are presented to verify the effectiveness of the proposed NSSS detection scheme. The simulation results show that the proposed NSSS detector achieves a considerable complexity reduction at the cost of some performance degradation, compared to the conventional NSSS detector.

Reduced Complexity Detection of Narrowband Secondary Synchronization Signal for NB-IoT Communication Systems

Abstract: Narrowband Internet of Things is one of the most promising technologies to support low cost, massive connection, deep coverage, and low power consumption. In this paper, a computationally efficient narrowband secondary synchronization signal detection method is proposed in the narrowband Internet of Things system. By decoupling the detection of complementary sequence and Zadoff–Chu sequence that make up the synchronization signal sequence, the search space of narrowband secondary synchronization signal hypotheses is reduced. Such a design strategy along with the use of the symmetric property of synchronization signals allows reduced-complexity synchronization signal detection in the narrowband Internet of Things system. Both theoretical and simulation results are provided to verify the usefulness of the proposed detector. It is shown via simulation results that the complexity of the proposed detection method is significantly reduced while producing some performance degradation, compared to the conventional detection method.

Application of Internet of Things Technology in Charging Station Operation and Maintenance Management System

Abstract: In the context of the global energy crisis and severe environmental pollution, the Chinese government is actively promoting the implementation and development of new energy vehicles. As an important supporting infrastructure for the development of new energy vehicles, charging stations have very important social value and economic benefits. This paper takes electric vehicles as an example to explore the application research of Internet of Things technology in the operation and maintenance management system of charging stations. This article mainly explains the concept and architecture of the Internet of Things technology from the network infrastructure and protocol architecture, detailed analysis and description of each layer in the protocol specification. This article tests the relevant parameters in the network system, including data loss rate test and data transmission time. This paper studies the construction and structure of electric vehicle charging stations, and then introduces the design principles and key technologies of the operation and maintenance management platform for electric vehicle charging stations. These key technologies include communication protocol, development language and development platform selection, software architecture design, etc. The experimental results show that the data loss rate of the networking system is less than 3%, and the transmission delay is about 9ms. Therefore, the data collected in the networking system designed in this paper has the characteristics of timeliness and accuracy, and conforms to the current data information. Requirements can be used in practical applications.