This paper presents a localization system robust against unreliable measurements and a resilient navigation system recovering from localization failures for Indy autonomous challenge (IAC). The IAC is a competition with full-scale autonomous race cars that drive at speeds up to 300 kph. Owing to high-speed and heavy vibration in the car, a GPS/INS system is prone to degrade causing critical localization errors, which leads to catastrophic accidents.In order to address this issue, we propose a robust localization system that probabilistically evaluates the credibility of multi-modal measurements. At a correction step of the Kalman filter, a degradation identification method with a novel hyper-parameter derived from Bayesian decision theory is introduced to choose the most credible measurement values in real-time. Since the racing condition is so harsh that even our robust localization method can fail for a short period of time, we present a resilient navigation system that enables the race car to continue to follow the race track in the event of a localization failure. Our system uses direct perception information in planning and execution until the completion of localization recovery.The proposed localization system is first validated in a simulation with real measurement data contaminated by large artificial noises. The experimental validation during an actual race is also presented. The last part of our paper shows the results from the real-world tests where our system recovers from failures and prevents accidents in real-time, which proves the resilience of the proposed navigation system.

In this paper, we propose a new beamforming design method to address the effect of beam squint in Terahertz communication. Conventional schemes for mitigating the beam squint have encountered challenges, such as high power consumption due to additional complex hardware or impractical computational complexity. To overcome the limitations, we propose a new analog beamforming technique, which does not require not only a high computational complexity but also additional hardware. Specifically, our proposed scheme performs analog beamforming at symmetrically shifted frequencies using a variable ϵ to create a robust wide beamformer in frequency domain, thereby minimizing the distortion of the array gain throughout the entire bandwidth. Furthermore, the value of ϵ is expressed in a closed form based on the lower bound of achievable spectral efficiency. Our simulation results show that the proposed scheme outperforms conventional hybrid beamformer and other techniques to deal with the beam squint.

In recent years, deep-learning-based point cloud registration methods have shown significant promise. Furthermore, learning-based 3D detectors have demonstrated their effectiveness in encoding semantic information from LiDAR data. In this paper, we introduce ELiOT, an end-to-end LiDAR odometry framework built on a transformer architecture. Our proposed Self-attention flow embedding network implicitly represents the motion of sequential LiDAR scenes, bypassing the need for 3D-2D projections traditionally used in such tasks. The network pipeline, composed of a 3D transformer encoder-decoder, has shown effectiveness in predicting poses on urban datasets. In terms of translational and rotational errors, our proposed method yields encouraging results, with 7.59% and 2.67% respectively on the KITTI odometry dataset. This is achieved with an end-to-end approach that foregoes the need for conventional geometric concepts.

We investigate the secrecy outage probability (SOP) of a downlink wiretap network consisting of a single legitimate base station (BS), multiple legitimate mobile stations (MSs), and multiple potential eavesdroppers (EVEs), where each EVE randomly attempts to overhear the data transmission with a certain probability. In particular, we consider an opportunistic feedback (OF) strategy in which each legitimate MS feeds their channel gain back to the BS for data reception only when its gain is greater than a certain threshold. We analyze a closed-form expression of the SOP under this strategy. As our main result, we demonstrate that the SOP of the OF strategy approaches that of the full feedback strategy as the number of legitimate MSs becomes large. It is worth noting that, for the first time, we mathematically characterize the SOP in this practical wiretap network setting having multiple potential EVEs.

Wireless avionics intra-communication (WAIC) refers to a wireless communication system among electronic components (e.g., sensors and actuators) that are integrated or installed in an aircraft and it is proposed to replace heavy and expensive wired communication cables. Recently, the use of a frequency band (4.2–4.4 GHz) for the WAIC (so-called, WAIC band) has been approved by international telecommunication union (ITU). Accordingly, several existing wireless protocols such as IEEE 802.11 and IEEE 802.15 are being considered as candidate techniques for the intra-avionics sensor network. In this paper, we perform a real field experiment to investigate wireless channel characteristics in intra-avionics sensor networks at the WAIC bands by a software-defined radio platform (universal software radio peripheral, USRP) and self-produced monopole antennas for the WAIC band. Through the experiment, we validated the feasibility of IEEE 802.11 protocol for the intra-avionics sensor network at the WAIC band in real aircraft environments. Furthermore, based on the measurement data, we evaluated the bit error rate (BER) performance of multiple antenna techniques where we considered the maximum ratio combining (MRC) for the multi-antenna receiver and the space-time block coding (STBC) for the multi-antenna transmitter.

In this letter, we consider the K-user bursty fading interference channel, where each user transmits data intermittently with a certain probability under the local channel state information assumption. In particular, we consider three different transmission techniques with fixed power: random transmission (RT), opportunistic transmission-based on generating interference (OT-1), and opportunistic transmission based on desired channel gain (OT-2). We mathematically analyze the average achievable rates of the three transmission techniques, which is the first theoretical result to the best our knowledge. The analysis is validated via extensive computer simulations. It is shown that the opportunistic transmission techniques (OT-1 and OT-2) result in better performance in terms of the achievable rate compared with the RT as well as the conventional non-bursty transmission technique.

In this paper, we investigate the effect of user scheduling and transmit power control on trade-off between spectral efficiency and energy efficiency in multi-cell uplink networks. We assume that each user adaptively controls the transmit power according to its generating interference to other cell base stations (BSs) and each BS schedules the user having the largest effective channel gain among users in a cell. The users transmit data with the peak power, Pmax, if the generating interference to other cell BSs is smaller than a particular threshold, With the joint interference-aware power control (IAPC) and user scheduling, the trade-off between spectral efficiency and energy efficiency becomes significantly improved as the number of users in each cell increased, compared with the conventional maximum signal-to-noise ratio (maxSNR) user scheduling and minimum interference-to-noise ratio (minINR) user scheduling. In addition, the power consumption becomes significantly reduced with the IAPC and user scheduling for a given spectral efficiency.