The existing multiple-input single-output (MISO) design to transmit data reliably to multiple mobile users (MUs) has become insufficient as MUs require fresh data, not just data. Therefore, in this paper, we consider multi-user MISO networks, where a base station (BS) equipped with multiple antennas serves MUs that want to maintain data freshness. To analyze the data freshness in this network, we first define the age-of-information (AoI) violation ratio, which is the ratio of duration that the AoI is larger than the AoI violation threshold to a sensing period. We then obtain the upper bound on the AoI violation ratio using the smooth maximum/minimum unit. We consider an optimization problem that minimizes the AoI violation ratio of multiple MUs. We propose a generalized power iteration (GPI) precoding algorithm to find a principal precoding vector that satisfies a first-order optimality condition of the optimization problem. Furthermore, for the scenario where the BS has the imperfect channel state information (CSI) of MUs, we provide the upper bound on the AoI violation time using the lower bound on the ergodic spectral efficiency, and also design the GPI precoding algorithm. Simulation results show proposed methods outperform baseline methods and demonstrate the effect of network parameters on the AoI violation probability.

With the development of the Internet of Things, the sensor usage has been elevated to a new level, and it becomes more crucial to maintain reliable sensor networks. In this article, we provide how to efficiently and reliably manage the sensor monitoring system for ensuring data freshness. A sensor transmits its sensing information regularly to the data center (DC), and the sensed information generally has the correlation over the space and the time. Hence, the accuracy of the estimated information from the sensed information decreases as the target location for information estimation is further away from the sensor or the Age of Information (AoI), the elapsed time from the information generation, increases. Therefore, by considering the effect of the AoI and the distance from the sensor on the estimation error, we newly define an error-tolerable sensing (ETS) coverage as the area that the estimated information at the DC is with smaller error than the target value. To analyze the impact of the AoI on the ETS coverage, we derive the$\eta $-coverage probability, which is the probability that the ETS coverage is greater than$\eta $ratio of the maximum sensor coverage, and the average ETS coverage. We also provide the optimal transmission power of the sensor, which minimizes the average energy consumption while guaranteeing certain level of the$\eta $-coverage probability. Numerical results validate the theoretical analysis and show the tendency of the optimal transmission power according to the maximum number of retransmissions. This article can pave the way to efficient design of the AoI-sensitive sensor networks.

In recent years, blockchain technology has been frequently exploited to address new security requirements for unmanned aerial vehicle (UAV)-assisted data collection (U-DC). However, the new latency to commit data to the blockchain ledger has emerged as a new issue. In this paper, therefore, we analyze the timely update probability (TUP) of the blockchain ledger, which is the probability that collected data from a UAV is updated in the blockchain within a given target latency. For analysis, we first define the TUP of the blockchain ledger in U-DC networks, using both the UAV communication and blockchain latencies. We then derive a closed-form expression of the TUP, and then validate our analysis. We conclude by exploring the impacts of some UAV communication and blockchain parameters on the TUP for their optimal deployment.

In both academia and industry, multi-user multiple-input single-output (MU-MISO) techniques have shown enormous gains in spectral efficiency by exploiting spatial degrees of freedom. So far, an underlying assumption in most of the existing MU-MISO design has been that all the users use infinite blocklength, so that they can achieve the Shannon capacity. This setup, however, is not suitable considering delay-constrained users whose blocklength tends to be finite. In this paper, we consider a heterogeneous setting in MU-MISO systems where delay-constrained users and delay-tolerant users coexist, called a DCTU-MISO network. To maximize the sum spectral efficiency in this system, we present the spectral efficiency for delay-tolerant users and provide a lower bound of the spectral efficiency for delay-constrained users. We consider an optimization problem that maximizes the sum spectral efficiency of delay-tolerant users while satisfying the latency constraint of delay-constrained users, and propose a generalized power iteration (GPI) precoding algorithm that finds a principal precoding vector. Furthermore, we extend a DCTU-MISO network to the multiple time slots scenario and propose a recursive GPI precoding algorithm. In simulation results, we validate proposed methods outperform baseline schemes and present the effect of network parameters on the average sum spectral efficiency.

Age of information (AoI) is a recently proposed metric for quantifying data freshness in real-time status monitoring systems where timeliness is of importance. In this paper, we explore the data freshness in the Hyperledger Fabric Blockchain-enabled monitoring network (HeMN) by leveraging the AoI metric. In HeMN, status updates from sources are transmitted through an uplink and recorded in a Hyperledger Fabric (HLF) network. To provide a stochastic guarantee of data freshness, we derive a closed-form of AoI violation probability by considering the transmission latency and the consensus latency. Then, we validate our analytic results through the implemented HLF platform. We also investigate the effect of the target successful transmission probability (STP) on the AoI violation probability.

In both academia and industry, the multiple-input multiple-output (MIMO) techniques have shown enormous gains in spectral efficiency by exploiting the spatial degrees of freedom. So far, an underlying assumption in most of existing multi-user multiple-input multiple-output (MU-MIMO) design has been that all the users in the system use infinite blocklength, so that they can achieve the Shannon capacity. This setup, however, is not suitable considering the presence of delay-constrained users whose the blocklength tends to be finite. In this paper, we consider a heterogeneous setting in a MU-MEMO system where delay tolerant users and delay constrained users coexist. To maximize the sum spectral efficiency in this system, we first present the spectral efficiencies for delay-tolerant user and delay-constrained user as the Rayleigh quotient. We then derive a first-order optimality condition of the optimization problem that maximizes the sum spectral efficiency of total users and satisfies the latency requirement of delay-constrained users, and propose the generalized power iteration preceding algorithm. In the simulation results, we prove that the proposed method outperforms baseline schemes.

Different from a terrestrial network, novel un-manned aerial vehicle (UAV) networks are necessary to efficiently serve aerial users (AUs) as well as ground users (GUs). In this paper, we model a base station (BS) antenna power gain, which is determined by the BS antenna tilt angle and the horizontal distance between BS and user (GU or AU). In order to efficiently serve both GUs and AUs, we propose two BS service schemes, inclusive-service base station (IS-BS) and exclusive-service base station (ES-BS) schemes. For each BS service scheme, we derive a network outage probability by taking into account the characteristics of the BS antenna power gain and channel components for line-of-sight (LoS) and non-line-of-sight (NLoS) environments. Finally, we show that the effect of the total BS density, the interfering BS density, and the user density on the optimal BS tilt angle and our proposed scheme.

Unlike terrestrial communications, unmanned aerial vehicle (UAV) communications have some advantages such as line-of-sight (LoS) environment and flexible mobility. However, the interference will be still inevitable. In this paper, we analyze the effect of the interference on the UAV communications by considering the LoS probability and different channel fadings for LoS and non-line-of-sight (NLoS) links, which are affected by the elevation angle of the communication link. We then derive a closed-form outage probability in the presence of an interfering node for all the possible scenarios and environments of main and interference links. After discussing the impacts of transmitting and interfering node parameters on the outage probability, we show the existence of the optimal height of the UAV that minimizes the outage probability. We also show the NLoS environment can be better than the LoS environment if the average received power of the interference is more dominant than that of the transmitting signal in UAV communications.