Impact of Array Configuration on Head-Mounted Display Performance at mmWave Bands
Immersing a user in life-like extended reality (XR) scenery using a head-mounted display (HMD) with a constrained form factor and hardware complexity requires remote rendering on a nearby edge server or computer. Millimeter-wave (mmWave) communication technology can provide sufficient data rate for wireless XR content transmission. However, mmWave channels exhibit severe sparsity in the angular domain. This means that distributed antenna arrays are required to cover a larger angular area and to combat outage during HMD rotation. At the same time, one would prefer fewer antenna elements/arrays for a lower complexity system. Therefore, it is important to evaluate the trade-off between the number of antenna arrays and the achievable performance to find a proper practical solution. This work presents indoor 28 GHz mmWave channel measurement data, collected during HMD mobility, and studies the dominant eigenmode (DE) gain. DE gain is a significant factor in understanding system performance since mmWave channel sparsity and eigenmode imbalance often results in provisioning the majority of the available power to the DE. Moreover, it provides the upper performance bounds for widely-adopted analog beamformers. We propose 3 performance metrics - gain trade-off, gain volatility, and minimum service trade-off - for evaluating the performance of a multi-array HMD and apply the metrics to indoor 28 GHz channel measurement data. Evaluation results indicate, that 3 arrays provide stable temporal channel gain. Adding a 4th array further increases channel capacity, while any additional arrays do not significantly increase physical layer performance.
Code (0)
등록된 구현이 없습니다.
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Channel Performance Metrics and Evaluation for XR Head-Mounted Displays with mmWave Arrays
Millimeter-wave (mmWave) technology holds the potential to revolutionize head-mounted displays (HMDs) by enabling high-speed wireless communication with nearby processing nodes, where complex video rendering can take pla…
Enhancing Facial Expression Recognition in Head-Mounted Displays with Synthetic Data
Facial expression recognition (FER) is crucial for social interaction in mixed reality environments that employ head-mounted displays (HMD). However, collecting FER data from head-mounted cameras (HMC) is challenging due…
Facial Expression RecognitionSlippage-robust Gaze Tracking for Near-eye Display
In recent years, head-mounted near-eye display devices have become the key hardware foundation for virtual reality and augmented reality. Thus head-mounted gaze tracking technology has received attention as an essential …
Subjective Quality Database and Objective Study of Compressed Point Clouds With 6DoF Head-Mounted Display
In this paper, we focus on subjective and objective Point Cloud Quality Assessment (PCQA) in an immersive environment and study the effect of geometry and texture attributes in compression distortion. Using a Head-Mounte…
Point Cloud Quality AssessmentQuantizationSubjective Quality Evaluation of Point Clouds Using a Head Mounted Display
This paper reports on a subjective quality evaluation of static point clouds encoded with the MPEG codecs V-PCC and G-PCC, the deep learning-based codec RS-DLPCC, and the popular Draco codec. 18 subjects visualized 3D re…