This paper proposes a successive interference cancellation (SIC) of independent component analysis (ICA) aided spatial division multiple access (SDMA) for Gaussian filtered frequency shift keying (GFSK) in Bluetooth low energy (BLE) systems. The typical SDMA scheme requires estimations of channel state information (CSI) using orthogonal pilot sequences. However, the orthogonal pilot is not embedded in the BLE packet. This fact motivates us to add ICA detector into BLE systems. In this paper, focusing on the covariance matrix of ICA outputs, SIC can be applied with Cholesky decomposition. Then, in order to address the phase ambiguity problems created by the ICA process, we propose a differential detection scheme based on the MAP algorithm. In practical scenarios, it is subject to carrier frequency offset (CFO) as well as symbol timing offset (STO) induced by the hardware impairments present in the BLE peripherals. The packet error rate (PER) performance is evaluated by computer simulations when BLE peripherals simultaneously communicate in the presence of CFO and STO.

With simultaneous multi-user transmissions, spatial division multiple access (SDMA) provides substantial throughput gain over the single user transmission. However, its implementation in WLANs with contention-based IEEE 802.11 MAC remains challenging. Problems such as coordinating and synchronizing the multiple users need to be solved in a distributed way. In this paper, we propose a distributed MAC protocol for WLANs with SDMA support. A dual-mode CTS responding mechanism is designed to accomplish the channel estimation and user synchronization required for SDMA. We analytically study the throughput performance of the proposed MAC, and dynamic parameter adjustment is designed to enhance the protocol efficiency. In addition, the proposed MAC protocol does not rely on specific physical layer realizations, and can work on legacy IEEE 802.11 equipment with slight software updates. Simulation results show that the proposed MAC outperforms IEEE 802.11 significantly, and that the dynamic parameter adjustment can effectively track the load variation in the network.