This dissertation proposes several communication systems utilizing power allocation and transmit precoding and a privacy-preserving robot vision system with a face-anonymizing framework. The works are categorized into three topics: (1) Spatial Spectral Reuse of LTE-LAA, (2) Asymmetric Hidden Termina...
This dissertation proposes several communication systems utilizing power allocation and transmit precoding and a privacy-preserving robot vision system with a face-anonymizing framework. The works are categorized into three topics: (1) Spatial Spectral Reuse of LTE-LAA, (2) Asymmetric Hidden Terminals Problem in LAA-WLAN coexistence, and (3) Privacy-Preserving Robot Vision with Face Anonymizing Framework. The first topic is to improve the spatial-spectral reuse of LTE License Assisted Access (LTELAA) coexisting with Wi-Fi. According to the specification of LTE-LAA, it should utilize different maximum energy detection thresholds depending on whether there is a single Wi-Fi device. However, there is no way for an LTE-LAA device to cognize whether a received signal is from LTE-LAA and Wi-Fi only within 4 s. Since Wi-Fi is already pervasive everywhere, LTE-LAA inevitably should utilize a low energy detection threshold, which leads to degradation of spatial-spectral reuse between LTE-LAA devices. To deal with this problem, we propose a lightweight but effective Wi-Fi preamble detection method for LTE-LAA, which allows LTELAA to dynamically change its maximum energy detection threshold. As a result, our proposal improves the spatial-spectral reuse of LTE-LAA while it protects Wi-Fi’s transmissions. In the second topic, we introduce the asymmetric hidden terminals (AHT) problem in LAAWLAN coexistence. This AHT problem occurs by the asymmetry in the setting of an energy detection threshold for LTE-LAA and Wi-Fi. From the perspective of medium access control (MAC) layer, we analyze the problem by using the conditional Markov chain, which reveals that the problem can severely degrade the performance of LTE-LAA and Wi-Fi in terms of throughput and delay. To alleviate the problem, we develop two methods to allow an LTE-LAA eNB to suppress Wi-Fi AP’s transmission during its transmission. Both methods control the interference from an LTE-LAA eNB to Wi-Fi APs with power allocation and transmit precoding technologies. The LTE-LAA eNB increases the interference to Wi-Fi APs, and thus the Wi-Fi APs can recognize LTE-LAA eNB’s transmission and defer their transmission. Since LTE-LAA and Wi-Fi can avoid unnecessary collisions, our proposals enhance their throughput and reduce their delay. The final topic proposes the privacy-preserving robot vision system to tackle privacy infringement by security robots. The security patrol robot market expected to grow significantly. In addition, as mobile surveillance devices, security robots are becoming more public spaces such as malls and offices. As security patrol robots are just starting to be deployed in public places, the privacy infringement issue begins to emerge by the public. Several articles reported that residents felt the robot was taking unnecessary photos of them, which resulted in that deployed security robot was suspended from its mission. To tackle the privacy issues, this dissertation develops a system to anonymize faces to preserve the privacy of people.
This dissertation proposes several communication systems utilizing power allocation and transmit precoding and a privacy-preserving robot vision system with a face-anonymizing framework. The works are categorized into three topics: (1) Spatial Spectral Reuse of LTE-LAA, (2) Asymmetric Hidden Terminals Problem in LAA-WLAN coexistence, and (3) Privacy-Preserving Robot Vision with Face Anonymizing Framework. The first topic is to improve the spatial-spectral reuse of LTE License Assisted Access (LTELAA) coexisting with Wi-Fi. According to the specification of LTE-LAA, it should utilize different maximum energy detection thresholds depending on whether there is a single Wi-Fi device. However, there is no way for an LTE-LAA device to cognize whether a received signal is from LTE-LAA and Wi-Fi only within 4 s. Since Wi-Fi is already pervasive everywhere, LTE-LAA inevitably should utilize a low energy detection threshold, which leads to degradation of spatial-spectral reuse between LTE-LAA devices. To deal with this problem, we propose a lightweight but effective Wi-Fi preamble detection method for LTE-LAA, which allows LTELAA to dynamically change its maximum energy detection threshold. As a result, our proposal improves the spatial-spectral reuse of LTE-LAA while it protects Wi-Fi’s transmissions. In the second topic, we introduce the asymmetric hidden terminals (AHT) problem in LAAWLAN coexistence. This AHT problem occurs by the asymmetry in the setting of an energy detection threshold for LTE-LAA and Wi-Fi. From the perspective of medium access control (MAC) layer, we analyze the problem by using the conditional Markov chain, which reveals that the problem can severely degrade the performance of LTE-LAA and Wi-Fi in terms of throughput and delay. To alleviate the problem, we develop two methods to allow an LTE-LAA eNB to suppress Wi-Fi AP’s transmission during its transmission. Both methods control the interference from an LTE-LAA eNB to Wi-Fi APs with power allocation and transmit precoding technologies. The LTE-LAA eNB increases the interference to Wi-Fi APs, and thus the Wi-Fi APs can recognize LTE-LAA eNB’s transmission and defer their transmission. Since LTE-LAA and Wi-Fi can avoid unnecessary collisions, our proposals enhance their throughput and reduce their delay. The final topic proposes the privacy-preserving robot vision system to tackle privacy infringement by security robots. The security patrol robot market expected to grow significantly. In addition, as mobile surveillance devices, security robots are becoming more public spaces such as malls and offices. As security patrol robots are just starting to be deployed in public places, the privacy infringement issue begins to emerge by the public. Several articles reported that residents felt the robot was taking unnecessary photos of them, which resulted in that deployed security robot was suspended from its mission. To tackle the privacy issues, this dissertation develops a system to anonymize faces to preserve the privacy of people.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.