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Space-ground integrated networks (SGINs) have attracted substantial research interests due to their wide area coverage capability, where spectrum sharing is employed between the satellite and terrestrial networks for improving the spectral efficiency (SE). We further improve the SE by conceiving a cellfree system in SGINs, where the full-duplex (FD) multi-antenna APs simultaneously provide downlink and uplink services at the same time and within the same frequency band. Furthermore, power domain (PD) non-orthogonal multiple access (NOMA) is employed as the multiple access (MA) technique in the cell-free system. To achieve a performance enhancement, the sum-rate maximization problem is formulated for jointly optimizing the power allocation factors (PAFs) of the NOMA downlink (DL), the uplink transmit power, and both the beamformer of the satellite and of the APs. Successive convex approximation (SCA) and semi-definite programming (SDP) are adopted to transform the resultant non-convex problem into an equivalent convex one. Our simulation results reveal that 1) our proposed system outperforms the well-known approaches (i.e., frequency division duplex (FDD) and small cell systems) in terms of its SE; 2) our proposed optimization algorithm significantly improves the networking performance; 3) the conceived SIC order design outperforms the fixed-order design at the same complexity.

Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted non-orthogonal multiple access (NOMA) communication systems are investigated in its vicinity, where a STAR-RIS is deployed within a predefined region for establishing communication links for users. Both beamformer-based NOMA and cluster-based NOMA schemes are employed at the multi-antenna base station (BS). For each scheme, the STAR-RIS deployment location, the passive transmitting and reflecting beamforming (BF) of the STAR-RIS, and the active BF at the BS are jointly optimized for maximizing the weighted sum-rate (WSR) of users. To solve the resultant non-convex problems, an alternating optimization (AO) algorithm is proposed, where successive convex approximation (SCA) and semi-definite programming (SDP) methods are invoked for iteratively addressing the non-convexity of each sub-problem. Numerical results reveal that 1) the WSR performance can be significantly enhanced by optimizing the specific deployment location of the STAR-RIS; 2) both beamformer-based and clusterbased NOMA prefer asymmetric STAR-RIS deployment.