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We consider an uplink integrated sensing and communications (ISAC) scenariowhere the detection of data symbols from multiple user equipment (UEs) occurssimultaneously with a three-dimensional (3D) estimation of the environment,extracted from the scattering features present in the channel state information(CSI) and utilizing the same physical layer communications air interface, asopposed to radar technologies. By exploiting a discrete (voxelated)representation of the environment, two novel ISAC schemes are derived withpurpose-built message passing (MP) rules for the joint estimation of datasymbols and status (filled/empty) of the discretized environment. The firstrelies on a modular feedback structure in which the data symbols and theenvironment are estimated alternately, whereas the second leverages a bilinearinference framework to estimate both variables concurrently. Both contributedmethods are shown via simulations to outperform the state-of-the-art (SotA) inaccurately recovering the transmitted data as well as the 3D image of theenvironment. An analysis of the computational complexities of the proposedmethods reveals distinct advantages of each scheme, namely, that the bilinearsolution exhibits a superior robustness to short pilots and channel blockages,while the alternating solution offers lower complexity with large number of UEsand superior performance in ideal conditions.

Integrated Sensing and Communications for 3D Object Imaging via Bilinear Inference