This article proposes an effective joint sidelink secondary synchronization signal (S-SSS) and carrier frequency offset (CFO) detection method for device-to-device-based new radio vehicle-to-everything networks. In order to improve the S-SSS and CFO detection performance, the proposed method uses a group-by-group correlation between four consecutive sidelink synchronization signals. The benefits and drawbacks of the proposed detection scheme are presented, and a theoretical analysis is derived, which is further discussed by means of simulation results. Both analytical results and simulations show that the proposed solution attains an improved detection performance using a group-wise correlation with slightly increased complexity, compared to existing detection algorithms.

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.

The oneM2M global initiative has been working to standardize horizontal machine-to-machine (M2M) and the Internet of Things (IoT) service layer specifications for globally interoperable M2M/IoT solutions. However, there exist a myriad of embedded sensor systems not complying with oneM2M, such as de facto IoT standards (e.g., AllJoyn and IoTivity). In this paper, we present our effort in global interworking of IoT systems across multiple M2M/IoT standards, in particular, on a global scale. By implementing specialized oneM2M entities for interworking, interworking proxy entities (IPEs), we demonstrate a promise of globally interoperable IoT systems interconnected with all kinds of embedded systems.

In this paper, we design an energy efficient MAC protocol for mobile sensor networks. In our MAC protocol, to reduce idle listening, each node has its listen-sleep schedule. A subset of nodes that follow the same schedule forms a virtual cluster. The network consists of multiple virtual clusters and nodes in one virtual cluster may follow a different listen- sleep schedule from that of nodes in another virtual cluster. Hence, to support a mobile sensor node that moves into a new virtual cluster that follows a different listen-sleep schedule, it is necessary to have a fast and energy efficient listen-sleep schedule adaptation protocol. To this end, in our MAC protocol, we utilize schedule information on border nodes between virtual clusters. This allows us to implement fast and energy efficient listen- sleep schedule adaptation, which consists of two main functions: energy efficient secondary listen period and smart scheduling adaptation. Simulation results show that our protocol can provide fast scheduling adaptation while achieving energy efficiency.