Pre-weighting based Contention Resolution Diversity Slotted ALOHA-like (PW-CRDSA-like) schemes with joint multi-user multi-slot detection (JMMD) algorithm are proposed to improve the throughput of random access (RA) in geostationary earth orbit (GEO) satellite networks. The packet and its replicas are weighted by different pre-weighting factors at each user terminal, and are sent in randomly selected slots within a frame. The correlation of channels between user terminals and satellite node in different slots are removed by using pre-weighting factors. At the gateway station, after the decoding processing of CRDSA, the combinations of remained signals in slots that can construct virtual multiple-input multiple-output (MIMO) signal models are found and decoded by the JMMD algorithm. Deadlock problems that can be equivalent to virtual MIMO signal models in the conventional CRDSA-like schemes can be effectively resolved, which improves the throughput of these CRDSA-like schemes. Simulation results show that the PW-CRDSA-like schemes with the JMMD significantly outperform the conventional CRDSA-like schemes in terms of the throughput under equal packet loss ratio (PLR) conditions (e.g. PLR =10-2), and as the number of the transmitted replicas increases, the throughput of the PW-CRDSA-like schemes also increases, and the normalized maximum throughput of the PW-CRDSA-5 (i.e., PW-CRDSA with 5 replicas) scheme can reach 0.95.

In this paper, performances of two different virtual multiple-input multiple-output (MIMO) transmission schemes — spatial multiplexing (SM) and space-time block coding (STBC) — in a correlated wireless sensor network are analyzed. By utilizing a complex Wishart distribution, we investigate the statistical properties of a correlated virtual MIMO channel between the sensors and data collector that is used in the performance analysis of each MIMO transmission mode. Distributed sensors then transmit their data cooperatively to the data collector by choosing a proper transmission mode adaptively based on the channel conditions and spatial correlation among the sensors. Furthermore, after analyzing the energy efficiencies of SM and STBC, we propose a new energy efficient mode switching rule between SM and STBC. Finally, by analytically deriving the required transmit energy of the proposed adaptive transmission scheme, the manner in which the spatial correlation influences the energy consumption is shown. This suggests a cooperating node scheduling protocol that makes energy consumption less sensitive to the variation of the spatial correlation.

The conventional semi-orthogonal user pairing algorithm in uplink virtual MIMO systems can be used to improve the total system throughput but it usually fails to maintain good throughput performance for users experiencing relatively poor channel conditions. A novel user paring algorithm is presented in this paper to solve this fairness issue. Based on our analysis of the MMSE receiver, a new criterion called “inverse selection” is proposed for use in conjunction with the semi-orthogonal user selection. Simulation results show that the proposed algorithm can significantly improve the throughput of users with poor channel condition at only a small reduction of the overall throughput.