Benefitting from the vast spatial degrees of freedom, the amalgamation of integrated sensing and communication (ISAC) and massive multiple-input multiple-output (MIMO) is expected to simultaneously improve spectral and energy efficiencies as well as the sensing capability. However, a large number of antennas deployed in massive MIMO-ISAC raises critical challenges in acquiring both accurate channel state information and target parameter information. To overcome these two challenges with a unified framework, we first analyze their underlying system models and then propose a novel tensor-based approach that addresses both the channel estimation and target sensing problems. Specifically, by parameterizing the high-dimensional communication channel exploiting a small number of physical parameters, we associate the channel state information with the sensing parameters of targets in terms of angular, delay, and Doppler dimensions. Then, we propose a shared training pattern adopting the same time-frequency resources such that both the channel estimation and target parameter estimation can be formulated as a canonical polyadic decomposition problem with a similar mathematical expression. On this basis, we first investigate the uniqueness condition of the tensor factorization and the maximum number of resolvable targets by utilizing the specific Vandermonde structure. Then, we develop a unified tensor-based algorithm to estimate the parameters including angles, time delays, Doppler shifts, and reflection/path coefficients of the targets/channels. In addition, we propose a segment-based shared training pattern to facilitate the channel and target parameter estimation for the case with significant beam squint effects. Simulation results verify our theoretical analysis and the superiority of the proposed unified algorithms in terms of estimation accuracy, sensing resolution, and training overhead reduction.

While two-way communication can improve the spectral efficiency of wireless networks, distances from the relay to the two users are usually asymmetric, leading to excessive wireless energy at the nearby user. To exploit the excessive energy, energy harvesting at user terminals is a viable option. Unfortunately, the exact gain brought by wireless power transfer (WPT) in two-way communication is currently unknown. To fill this gap, in this paper, the achievable rate region of wirelessly powered two-way communication with a fixed relay is derived. Not only this newly established result is shown to enclose the existing achievable rate region of two-way relay channel without energy harvesting but also the gain is precisely quantified. On the other hand, it is well-known that a major obstacle to WPT is the path-loss. By endowing the relay with mobility, the distances between the relay and users can be varied, thus providing a potential solution to combat pathloss at the expense of energy for transmission. To characterize the consequence brought by such a scheme, a pair of inner and outer bounds to the achievable rate region of wirelessly powered two-way communication under a mobile relay is further derived. By comparing the exact achievable rate region for the fixed relay case and the achievable rate bounds for the mobile relay case, it is possible to quantify the relative advantage of spending energy on moving versus on transmission in wirelessly powered two-way communication.