Exact Payload-Decoupling Conditions for Pilot-Only BEM Channel Estimation With Application to OTFS
本文针对高移动性双散射信道中的载荷污染问题,提出了零载荷干扰条件及导频、保护和数据布局规则,确保了基于BEM的信道估计独立于载荷。
本文针对高移动性双散射信道中的载荷污染问题,提出了零载荷干扰条件及导频、保护和数据布局规则,确保了基于BEM的信道估计独立于载荷。
研究探讨了通过5G NR-V2X直连通信分享感知信息对道路安全的影响,采用网络级仿真分析了不同对象选择策略下的通信可靠性、延迟及信道占用情况。
本文提出了一种利用非线性堆叠智能超表面的极大MIMO系统,直接在无线传输的数据上执行二分类任务,以简化硬件复杂度并实现波域中的低复杂度学习。
This work addresses the challenge of simultaneously achieving system efficiency, low communication overhead, safe execution, and scalability in large-scale urban traffic management. To this end, we propose VeloCity, a decentralized spatiotemporal trajectory planning framework that, for the first time, supports arbitrary complex urban road networks. In VeloCity, each connected autonomous vehicle autonomously generates conflict-free, dynamically feasible trajectories that minimize travel time, based on a spatiotemporal slot reservation table provided by local coordinators. The approach requires no scenario-specific customization and integrates distributed spatiotemporal profile optimization with a generic road topology adaptation mechanism. Large-scale simulations in Tokyo, Manhattan, Rome, and Bologna demonstrate significant reductions in both travel time and delay variance, effectively prevent gridlock, and exhibit exceptional scalability and performance advantages.
This paper investigates network-level integrated sensing and communication (ISAC) under two fundamentally different topology configurations: cell-free massive MIMO (CF-mMIMO) and multi-cell massive MIMO (MC-mMIMO). A unified OFDM-based waveform is adopted for both architectures as the key enabler for ISAC functionalities. The CF system exploits distributed access points (APs) and a scalable user-target-centric operation, whereas the MC system relies on co-located transmit-receive arrays with conventional cell-centric deployment. For both architectures, we derive a GLRT-based sensing detector and the corresponding sensing SNR expressions. We then examine a series of case studies investigating how the number of OFDM subcarriers, the transceiver allocation strategy, and the antenna/node distribution across the network affect the sensing performance. The results consistently demonstrate that CF-mMIMO provides more robust and higher sensing performance across most tested scenarios, particularly when transmit resources or antenna elements are spatially distributed. These findings highlight the inherent advantages of CF deployments for next-generation ISAC networks.
本文针对高移动性双散射信道中的载荷污染问题,提出了零载荷干扰条件及导频、保护和数据布局规则,确保了基于BEM的信道估计独立于载荷。
研究探讨了通过5G NR-V2X直连通信分享感知信息对道路安全的影响,采用网络级仿真分析了不同对象选择策略下的通信可靠性、延迟及信道占用情况。
本文提出了一种利用非线性堆叠智能超表面的极大MIMO系统,直接在无线传输的数据上执行二分类任务,以简化硬件复杂度并实现波域中的低复杂度学习。
This work addresses the challenge of simultaneously achieving system efficiency, low communication overhead, safe execution, and scalability in large-scale urban traffic management. To this end, we propose VeloCity, a decentralized spatiotemporal trajectory planning framework that, for the first time, supports arbitrary complex urban road networks. In VeloCity, each connected autonomous vehicle autonomously generates conflict-free, dynamically feasible trajectories that minimize travel time, based on a spatiotemporal slot reservation table provided by local coordinators. The approach requires no scenario-specific customization and integrates distributed spatiotemporal profile optimization with a generic road topology adaptation mechanism. Large-scale simulations in Tokyo, Manhattan, Rome, and Bologna demonstrate significant reductions in both travel time and delay variance, effectively prevent gridlock, and exhibit exceptional scalability and performance advantages.
This paper investigates network-level integrated sensing and communication (ISAC) under two fundamentally different topology configurations: cell-free massive MIMO (CF-mMIMO) and multi-cell massive MIMO (MC-mMIMO). A unified OFDM-based waveform is adopted for both architectures as the key enabler for ISAC functionalities. The CF system exploits distributed access points (APs) and a scalable user-target-centric operation, whereas the MC system relies on co-located transmit-receive arrays with conventional cell-centric deployment. For both architectures, we derive a GLRT-based sensing detector and the corresponding sensing SNR expressions. We then examine a series of case studies investigating how the number of OFDM subcarriers, the transceiver allocation strategy, and the antenna/node distribution across the network affect the sensing performance. The results consistently demonstrate that CF-mMIMO provides more robust and higher sensing performance across most tested scenarios, particularly when transmit resources or antenna elements are spatially distributed. These findings highlight the inherent advantages of CF deployments for next-generation ISAC networks.