In-loop filters have been comprehensively explored during the development of video coding standards due to their remarkable noise-reduction capabilities.In the early stage of video coding,in-loop filters,such as the deblocking filter,sample adaptive offset,and adap-tive loop filter,were performed separately for each component.Recently,cross-component filters have been studied to improve chroma fidel-ity by exploiting correlations between the luma and chroma channels.This paper introduces the cross-component filters used in the state-of-the-art video coding standards,including the cross-component adaptive loop filter and cross-component sample adaptive offset.Cross-component filters aim to reduce compression artifacts based on the correlation between different components and provide more accurate pixel reconstruction values.We present their origin,development,and status in the current video coding standards.Finally,we conduct discussions on the further evolution of cross-component filters.
The advent of 6G wireless networks promises unprecedented connectivity,supporting ultra-high data rates,low latency,and massive device connectivity.However,these ambitious goals introduce significant challenges,particularly in channel estimation due to complex and dynamic propagation environments.This paper explores the concept of channel knowledge maps(CKMs) as a solution to these challenges.CKMs enable environment-aware communications by providing location-specific channel information,reducing reliance on real-time pilot measurements.We categorize CKM construction techniques into measurement-based,model-based,and hybrid methods,and examine their key applications in integrated sensing and communication(ISAC) systems,beamforming,trajectory optimization of unmanned aerial vehicles(UAVs),base station(BS) placement,and resource allocation.Furthermore,we discuss open challenges and propose future research directions to enhance the robustness,accuracy,and scalability of CKM-based systems in the evolving 6G landscape.
Along with the proliferating research interest in semantic communication(SemCom),joint source channel coding(JSCC)has domi-nated the attention due to the widely assumed existence in efficiently delivering information semantics.Nevertheless,this paper challenges the conventional JSCC paradigm and advocates for adopting separate source channel coding(SSCC)to enjoy a more underlying degree of free-dom for optimization.We demonstrate that SSCC,after leveraging the strengths of the Large Language Model(LLM)for source coding and Er-ror Correction Code Transformer(ECCT)complemented for channel coding,offers superior performance over JSCC.Our proposed framework also effectively highlights the compatibility challenges between SemCom approaches and digital communication systems,particularly concern-ing the resource costs associated with the transmission of high-precision floating point numbers.Through comprehensive evaluations,we es-tablish that assisted by LLM-based compression and ECCT-enhanced error correction,SSCC remains a viable and effective solution for mod-ern communication systems.In other words,separate source channel coding is still what we need.
Wireless local area network (WLAN) witnesses a very fast growth in the past 20 years by taking the maximum throughput as the key technical objective. However, the quality of experience (QoE) is the most important concern of wireless network users. In this article, we point out that poor QoE is the most challenging problem of the current WLAN, and further analyze the key technical problems that cause the poor QoE of WLAN, including fully distributed networking architecture, chaotic random access, awkward ``high capability'', coarse-grained QoS architecture, ubiquitous and complicated interference, ``no place'' for artificial intelligence (AI), and heavy burden of standard evolving. To the best of our knowledge, this is the first work to point out that poor QoE is the most challenging problem of the current WLAN, and the first work to systematically analyze the technical problems that cause the poor QoE of WLAN. We highly suggest that achieving high experiences (HEX) be the key objective of the next generation WLAN.
A cooperative passive sensing framework for millimeter wave(mmWave) communication systems is proposed and demonstrated in a scenario with one mobile signal blocker. Specifically, in the uplink communication with at least two transmitters, a cooperative detection method is proposed for the receiver to track the blocker's trajectory, localize the transmitters and detect the potential link blockage jointly. To facilitate detection, the receiver collects the signal of each transmitter along a line-of-sight(LoS) path and a non-line-of-sight(NLoS) path separately via two narrow-beam phased arrays. The NLoS path involves scattering at the mobile blocker, allowing its identification through the Doppler fre-quency. By comparing the received signals of both paths, the Doppler frequency and angle-of-arrival(AoA) of the NLoS path can be estimated. To resolve the blocker's trajectory and the transmitters' locations, the receiver should continuously track the mobile blocker to accumulate suffi-cient numbers of the Doppler frequency and AoA versus time observations. Finally, a gradient-descent-based algorithm is proposed for joint de-tection. With the reconstructed trajectory, the potential link blockage can be predicted. It is demonstrated that the system can achieve decimeter-level localization and trajectory estimation, and predict the blockage time with an error of less than 0.1 s.
