Indoor pedestrian tracking extends location-based services to indoor environments where GPS signal is rarely detected. Typical indoor localization method is Wi-Fi-based positioning system, which is ...practical showing accuracy and extending coverage. However, it involves significant costs of installing and managing wireless access points. A practical indoor pedestrian-tracking approach should consider the absence of any infrastructure or pretrained database. In this paper, we present a smartphone-based pedestrian dead reckoning, SmartPDR, which tracks pedestrians through typical dead reckoning approach using data from inertial sensors embedded in smartphones. SmartPDR does not require any complex and expensive additional device or infrastructure that most existing pedestrian tracking systems rely on. The proposed system was implemented on off-the-shelf smartphones and the performance was evaluated in several buildings. Despite inherent localization errors from low-cost noisy sensors and complicated human movements, SmartPDR successfully tracks indoor user's location, which is confirmed from the experimental results with reasonable location accuracy. Indoor pedestrian tracking system using smartphone inertial sensors can be a promising methodology validating its practical usage through real deployment.
Recently, an unmanned aerial vehicle (UAV) has been widely adopted to make efficient use of network resources in such areas as internet of things (IoT), sensor networks and three dimensional (3D) ...wireless networks. Especially, in wireless sensor networks (WSNs) where energy consumption of sensors in data transmission is the most conspicuous feature, data collection by UAV provides a promising solution. To address this issue, we consider a UAV-enabled WSN, where a UAV is dispatched to collect data from sensors distributed in networks. We formulate an optimization problem to maximize the minimum residual energy of sensors after data transmission for energy-efficient UAV routing subject to data collection and UAV traveling distance constraints. To solve the non-convex optimization problem, we first derive a feasible solution, i.e., the shortest UAV route that guarantees data collection at all the sensors, where a Voronoi diagram is modified to find a set of UAV hovering locations. The proposed algorithm preferentially determines each UAV hovering location at Voronoi vertex so that UAV can collect data from as many adjacent sensors as possible. Then with an initial shortest UAV route, a UAV route is proposed by adjusting each UAV hovering location sequentially based on sensor energy status, which is easily accomplished by the properties of Voronoi diagram. Lastly, to find the proposed solution more quickly, we propose a sensor-energy based initial UAV route determination method. Simulation results are provided to validate the performance of our proposed algorithm, and to compare with other UAV route determination schemes.
Research and development of heterogeneous small cell in cellular network accommodates the proliferation of data-hungry devices and applications. Meanwhile, for challenges in providing high-data-rate ...transmission in poor coverage area, utilizing unmanned aerial vehicles (UAVs) provides a promising solution attracting tremendous attention. However, tight integration of UAVs creates an obstruction in existing network to acquire high efficient resource utilization, which needs investigation in 3 D network architecture. In this letter, we propose a resource allocation optimization mechanism to minimize mean packet transmission delay in 3 D cellular network with multi-layer UAVs. Numerical results demonstrate effectiveness of the proposed algorithm, where optimal spectrum and power allocation can provide minimum packet transmission delay.
Along with enhanced mobile broadband and ultra-reliable low latency communication, massive connectivity has been one of the key requirements for enabling technologies of 5G. For IoT, low power ...consumption and wide area coverage for end devices (ED) are important figures of merit, for which LoRa, SigFox and Narrow Band-IoT are dominant technologies. In this letter, we analyze LoRa systems for increasing average system packet success probability (PSP) under unslotted ALOHA random access protocol. The lower bound for average system PSP is derived by stochastic geometry. And it is shown that the average system PSP can be maximized by properly allocating spreading factor (SF) to each traffic, which also maximizes connectivity of EDs. We formulate an optimization problem for maximizing the average system PSP to propose a sub-optimal SF allocation scheme to each traffic. Analysis on PSP is validated through simulations, and comparison with existing schemes reveals that our proposed scheme achieves the highest PSP and so the maximum connectivity.
In this letter, we analyze the coexistence performance of Wi-Fi and cellular networks with different listen-before-talk (LBT) procedures in the unlicensed spectrum. For this analysis, the behavior of ...a cellular base station is modeled as a Markov chain that is combined with Bianchi's Markov model depicting the behavior of a Wi-Fi access point. The proposed mathematical framework finds the optimal contention window size of cellular base stations, which maximizes the total throughput of both networks while satisfying the required throughput of each network. Numerical results show the validity of adjustment in the parameter of LBT.
In this letter, we formulate a downlink packet scheduling problem for proportional fairness in orthogonal frequency division multiple access with frequency division multiple access (OFDMA) systems to ...derive necessary conditions for optimality, which results in efficient subcarrier and power allocation algorithms. Simulation results reveal that our proposed algorithm achieves the tradeoff between system throughput and fairness
Heterogeneous wireless networks where several systems with different bands coexist for multimedia service are currently in service and will be widely adopted to support various traffic demand. Under ...heterogeneous networks, a mobile station can transmit over multiple and simultaneous radio access technologies (RATs) such as WLAN, HSPA, and WCDMA LTE. Also, cognitive radio for the efficient use of underutilized/unused frequency band is successfully implemented in some networks. In this letter, we address such operational issues as air interface and band selection for a mobile and power allocation to the chosen links. An optimal solution is sought and analyzed and a distributed joint allocation algorithm is proposed to maximize total system capacity. We investigate the benefit of multiple transmissions by multiple RATs over a single transmission by a single RAT at a time, which can be interpreted as network diversity. Numerical results validate the performance enhancement of our proposed algorithm.
This letter extends the proportional fair (PF) scheduling proposed in the high data rate (HDR) system to multicarrier transmission systems. It is known that the PF allocation (F. P. Kelly et al. ...(1998)) results in the maximization of the sum of logarithmic average user rates. We propose a PF scheduling that assigns users to each carrier while maximizing the sum of logarithmic average user rates.
For random access (RA) procedure in LTE-based systems, timing advance (TA) value is included for a device to adjust its uplink timing synchronization. In this letter, we propose a simple prioritized ...energy-efficient RA (EERA) scheme for stationary Internet of Things networks by utilizing TA value. We analyze the collision probability and average energy consumption to show the effectiveness of the EERA scheme. Performance evaluation shows that the proposed EERA scheme not only has lower collision probability but also consumes less energy than other RA schemes under practical simulation environments.
In this letter, we focus on joint subcarrier and power allocation in the uplink of an OFDMA system. Our goal is to maximize the rate-sum capacity in the uplink. For the purpose, we formulate an ...optimization problem subject to subcarrier and power constraints and draw necessary conditions for optimality, from which we derive joint subcarrier and power allocation algorithms. Simulation results show that our proposed scheme enhances the system capacity, providing almost near optimal solutions with low computational burden.
