{"title":"具有过时 CSI 的 RIS 辅助网络的时变信道估计:超越相干时间的视角","authors":"Souvik Deb, Sasthi C. Ghosh","doi":"arxiv-2408.17128","DOIUrl":null,"url":null,"abstract":"The channel estimation (CE) overhead for unstructured multipath-rich channels\nincreases linearly with the number of reflective elements of reconfigurable\nintelligent surface (RIS). This results in a significant portion of the channel\ncoherence time being spent on CE, reducing data communication time.\nFurthermore, due to the mobility of the user equipment (UE) and the time\nconsumed during CE, the estimated channel state information (CSI) may become\noutdated during actual data communication. In recent studies, the timing for CE\nhas been primarily determined based on the coherence time interval, which is\ndependent on the velocity of the UE. However, the effect of the current channel\ncondition and pathloss of the UEs can also be utilized to control the duration\nbetween successive CE to reduce the overhead while still maintaining the\nquality of service. Furthermore, for muti-user systems, the appropriate\ncoherence time intervals of different users may be different depending on their\nvelocities. Therefore CE carried out ignoring the difference in coherence time\nof different UEs may result in the estimated CSI being detrimentally outdated\nfor some users. In contrast, others may not have sufficient time for data\ncommunication. To this end, based on the throughput analysis on outdated CSI,\nan algorithm has been designed to dynamically predict the next time instant for\nCE after the current CSI acquisition. In the first step, optimal RIS phase\nshifts to maximise channel gain is computed. Based on this and the amount of\ndegradation of SINR due to outdated CSI, transmit powers are allocated for the\nUEs and finally the next time instant for CE is predicted such that the\naggregated throughput is maximized. Simulation results confirm that our\nproposed algorithm outperforms the coherence time-based strategies.","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Time varying channel estimation for RIS assisted network with outdated CSI: Looking beyond coherence time\",\"authors\":\"Souvik Deb, Sasthi C. 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Furthermore, for muti-user systems, the appropriate\\ncoherence time intervals of different users may be different depending on their\\nvelocities. Therefore CE carried out ignoring the difference in coherence time\\nof different UEs may result in the estimated CSI being detrimentally outdated\\nfor some users. In contrast, others may not have sufficient time for data\\ncommunication. To this end, based on the throughput analysis on outdated CSI,\\nan algorithm has been designed to dynamically predict the next time instant for\\nCE after the current CSI acquisition. In the first step, optimal RIS phase\\nshifts to maximise channel gain is computed. Based on this and the amount of\\ndegradation of SINR due to outdated CSI, transmit powers are allocated for the\\nUEs and finally the next time instant for CE is predicted such that the\\naggregated throughput is maximized. 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引用次数: 0
摘要
非结构化多径信道的信道估计(CE)开销与可重构智能表面(RIS)的反射元素数量呈线性增长。此外,由于用户设备(UE)的移动性和 CE 期间消耗的时间,估计的信道状态信息(CSI)在实际数据通信期间可能会过时。在最近的研究中,CE 的定时主要是根据相干时间间隔确定的,而相干时间间隔取决于 UE 的速度。不过,也可以利用 UE 当前信道条件和路径损耗的影响来控制连续 CE 之间的持续时间,从而在保持服务质量的同时减少开销。此外,对于多用户系统,不同用户的适当相干时间间隔可能因其位置而异。因此,忽略不同 UE 相干时间差异的 CE 可能会导致估计的 CSI 对某些用户不利地过时。相反,其他用户可能没有足够的时间进行数据通信。为此,基于对过时 CSI 的吞吐量分析,我们设计了一种算法来动态预测当前 CSI 获取后的下一个CE 时间瞬时。第一步,计算最佳 RIS 相移,以实现信道增益最大化。在此基础上,再根据过时 CSI 导致的 SINR 下降量,为 UE 分配发射功率,最后预测 CE 的下一个时间点,从而最大限度地提高综合吞吐量。仿真结果证实,我们提出的算法优于基于相干时间的策略。
Time varying channel estimation for RIS assisted network with outdated CSI: Looking beyond coherence time
The channel estimation (CE) overhead for unstructured multipath-rich channels
increases linearly with the number of reflective elements of reconfigurable
intelligent surface (RIS). This results in a significant portion of the channel
coherence time being spent on CE, reducing data communication time.
Furthermore, due to the mobility of the user equipment (UE) and the time
consumed during CE, the estimated channel state information (CSI) may become
outdated during actual data communication. In recent studies, the timing for CE
has been primarily determined based on the coherence time interval, which is
dependent on the velocity of the UE. However, the effect of the current channel
condition and pathloss of the UEs can also be utilized to control the duration
between successive CE to reduce the overhead while still maintaining the
quality of service. Furthermore, for muti-user systems, the appropriate
coherence time intervals of different users may be different depending on their
velocities. Therefore CE carried out ignoring the difference in coherence time
of different UEs may result in the estimated CSI being detrimentally outdated
for some users. In contrast, others may not have sufficient time for data
communication. To this end, based on the throughput analysis on outdated CSI,
an algorithm has been designed to dynamically predict the next time instant for
CE after the current CSI acquisition. In the first step, optimal RIS phase
shifts to maximise channel gain is computed. Based on this and the amount of
degradation of SINR due to outdated CSI, transmit powers are allocated for the
UEs and finally the next time instant for CE is predicted such that the
aggregated throughput is maximized. Simulation results confirm that our
proposed algorithm outperforms the coherence time-based strategies.