Collaborative access points (APs) enabled cell-free networks can provide stable and uniform communication services for all user locations, making them a promising network architecture for the sixth-generation (6G) mobile communication systems. While the performance of pure cell-free networks has been extensively studied, it remains unclear whether deploying large-scale cell-free APs in legacy cellular networks can effectively boost communication performance. Besides, the realization of a cell-free network is considered to be a gradual long-term evolutionary process in which APs will be incrementally introduced and form a hybrid communication network with the existing cellular base stations (BSs). Such a collaboration will bridge the gap between the established cellular network and the innovative cell-free network. Therefore, hybrid cellular and cell-free networks (HCCNs) emerge as a feasible solution for advancing cell-free network development, and it is worthwhile to further explore its performance limits. Different from heterogeneous networks or multipoint coordinated networks, the characterization of HCCNs needs to take both inter- and intra-layer collaboration into account. This paper presents a stochastic geometry-based HCCN model to analyze the distributions of signal and interference and reveal their mutual coupling. Specifically, in order to benefit the user equipments (UEs) from both the cellular BSs and the cell-free APs, a conjugate beamforming design is employed, and the aggregated signal is analyzed using moment matching. Then, the coverage probability of the hybrid network is characterized by deriving the Laplace transforms and their higher-order derivatives of interference components. Furthermore, the average achievable rate of the hybrid network over channel fading is derived based on the interference coupling analysis. Simulation results demonstrate that compared to traditional cellular networks, HCCN effectively narrows communication quality differences between different UEs and improves overall communication performance.

As one of the key usage scenarios for the sixth generation (6G) wireless networks, integrated sensing and communication (ISAC) provides an efficient framework to achieve simultaneous wireless sensing and communication. However, traditional wireless sensing techniques mainly rely on line-of-sight (LoS) assumptions, i.e., the sensing targets are directly visible to both the sensing transmitter and receiver. This prevents ISAC systems from being applied in complex environments such as the urban low-altitude airspace, which usually suffers from signal blockage and non-line-of-sight (NLoS) multipath propagation. To address this challenge, in this paper, we propose a novel approach to enable environment-aware NLoS ISAC by leveraging the new technique called channel knowledge map (CKM), which was originally proposed for environment-aware wireless communications. One major novelty of our proposed method is that the same CKM built for wireless communication can be directly used to enable NLoS wireless sensing, thus enjoying the benefits of “killing two birds with one stone”. To this end, the sensing targets are treated as virtual user equipment (UE), and the wireless communication channel priors are transformed into the sensing channel priors, allowing one single CKM to serve dual purposes. We illustrate our proposed framework using a specific CKM called channel angle-delay map (CADM). Specifically, the proposed framework utilizes CADM to derive angle-delay priors of the sensing channel by exploiting the relationship between communication and sensing angle-delay distributions, enabling sensing target localization in the challenging NLoS environment. Extensive simulation results demonstrate significant performance improvements over classic geometry-based sensing methods, which are further validated by Cramér-Rao Lower Bound (CRLB) analysis.

Channel gain map (CGM) is a promising technique that enables the environment-aware communications by providing a priori channel gain information for users at arbitrary locations. The construction of CGM can be viewed as spatial channel prediction from the communication perspective, which motivates the channel model-based construction algorithm. On the other hand, it can also be viewed as spatial data interpolation from the geostatistic perspective, where a bunch of model-free methods can be adopted. This paper compares model-based and model-free approaches for CGM construction. We extend the existing model-based channel prediction by introducing a multi-mode channel model to address the spatial inconsistency issue in conventional models. The model-based methods are then compared with various model-free spatial interpolation methods, including a deep learning method. The results show that the channel model may introduce substantial bias for CGM construction in complex environments.

Cell-free wireless communication is envisioned as one of the most promising network architectures, which can achieve stable and uniform communication performance while improving the system energy and spectrum efficiency. The deployment of cell-free networks is envisioned to be a long-term evolutionary process, in which cell-free access points (APs) will be gradually introduced into the communication network and collaborate with the existing cellular base stations (BSs). To further explore the performance limits of hybrid cellular and cell-free networks, this paper develops a hybrid network model based on stochastic geometric toolkits, which reveals the coupling of the signal and interference from both the cellular and cell-free networks. Specifically, the conjugate beamforming is applied in hybrid cellular and cell-free networks, which enables user equipment (UE) to benefit from both cellular BSs and cell-free APs. The aggregate signal received from the hybrid network is approximated via moment matching, and coverage probability is characterized by deriving the Laplace transform of the interference. The analysis of signal strength and coverage probability is verified by extensive simulations.

Thanks to the great potential to alleviate the intercell interference issue, cell-free wireless network is regarded as one of the most promising networking architectures in the future. In the meantime, the dramatic increase in the number of wireless devices and their diversified communication rate requirements pose new challenges for cell-free networks. In this article, we integrate the new symbiotic radio (SR) transmission technique into cell-free networks. In particular, spectral- and energy-efficient passive backscatter communication in SR is achieved by passive reflective beamforming over multiple reconfigurable intelligent surfaces (RISs). On the one hand, distributed access points (APs) in cell-free network collaboratively perform active communication through direct links, and on the other hand, RISs reuse the spectrum and energy of active communication to passively backscatter its own information-bearing signal. Considering the coexistence of active and passive communication demands, we define the rate region of the RIS-based cell-free SR system as the union of all rate pairs achieved by the active and passive communication devices. To characterize the achievable rate region, we formulate an optimization problem to maximize the passive communication rate given a minimum active rate constraint, by jointly optimizing the active transmit beamforming and passive reflective beamforming. An efficient alternating algorithm is proposed to solve the formulated problem. Finally, simulation results are presented to show the rate region of RIS-based cell-free SR systems and demonstrate the effectiveness of the proposed joint beamforming algorithm.

Cell-free massive MIMO and symbiotic radio communication have been recently proposed as the promising beyond fifth-generation (B5G) networking architecture and transmission technology, respectively. To reap the benefits of both, this paper studies cell-free symbiotic radio communication systems, where a number of cell-free access points (APs) cooperatively send primary information to a receiver, and simultaneously support the passive backscattering communication of the secondary backscatter device (BD). We first derive the achievable communication rates of the active primary user and passive secondary user under the assumption of perfect channel state information (CSI), based on which the transmit beamforming of the cell-free APs is optimized to characterize the achievable rate-region of cell-free symbiotic communication systems. Furthermore, to practically acquire the CSI of the active and passive channels, we propose an efficient channel estimation method based on two-phase uplink-training, and the achievable rate-region taking into account CSI estimation errors is further characterized. Simulation results are provided to show the effectiveness of our proposed beamforming and channel estimation methods.

Symbiotic radio has emerged as a promising technology for spectrum- and energy-efficient wireless communications, where the passive secondary backscatter devices (BDs) reuse not only the spectrum but also the power of the active primary users to transmit their own information. In return, the primary communication links can be enhanced by the additional multipaths created by the BDs. This is known as the mutualism relationship of symbiotic radio. However, due to the severe double-fading attenuation of the passive backscattering links, the enhancement of the primary link provided by one single BD is extremely limited. To address this issue and enable full mutualism of symbiotic radio, in this paper, we study multiple-input multiple-output (MIMO) symbiotic radio communication systems with massive BDs. We first derive the achievable rates of the primary active communication and secondary passive communication, and then consider the asymptotic regime as the number of BDs goes large, for which closed-form expressions are derived to reveal the relationship between the primary and secondary communication rates. Furthermore, the precoding optimization problem is studied to maximize the primary communication rate while guaranteeing that the secondary communication rate is no smaller than a certain threshold. Simulation results are provided to validate our theoretical studies.

Symbiotic radio is a promising technology to achieve spectrum-and energy-efficient wireless communications, where the secondary backscatter device (BD) leverages not only the spectrum but also the power of the primary signals for its own information transmission. In return, the primary communication link can be enhanced by the additional multipaths created by the BD. This is known as the mutualism relationship of symbiotic radio. However, as the backscattering link is much weaker than the direct link due to double attenuations, the improvement of the primary link brought by one single BD is extremely limited. To address this issue and enable full mutualism of symbiotic radio, in this paper, we study symbiotic radio with massive number of BDs. For symbiotic radio multiple access channel (MAC) with successive interference cancellation (SIC), we first derive the achievable rate of both the primary and secondary communications, based on which a receive beamforming optimization problem is formulated and solved. Furthermore, considering the asymptotic regime of massive number of BDs, closed-form expressions are derived for the primary and the secondary communication rates, both of which are shown to be increasing functions of the number of BDs. This thus demonstrates that the mutualism relationship of symbiotic radio can be fully exploited with massive BD access.