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[SMS] Aprox_MU_MIMO_Q_model DL : 0: The model is built upon the assumption that the probabil- ity distribution of available destinations among the buered frames at the Base Station (BS) is approximately the same as the probability distribution of the trac arriving to the BS, this is, the amount of trac directed to each MN with respect to the total trac load. This assumption leads to a simple, but accurate, queueing model for Multi- user MIMO systems that accounts for the impact of a nite number of active MNs in non-saturated conditions. The model is easily applicable to any Multi-user MIMO scenario given that the probability density function of the post-processing SINR (Signal to Interference and Noise Ratio) for each MN is known.
Date : 2025-12-17 Size : 90kb User : ImranKhan
[SMS] CAMSAM_05_TUI DL : 0: If SDMA is used on the downlink of a multi-user MIMO system, either long-term or short-term channel state information has to be available at the base station (BS) to faciliate the joint precoding of the signals intended for the different users. Precoding is used to efficiently eliminate or suppressmulti-user interference (MUI) via beamforming or by using ”dirty-paper” codes. It also allows us to performmost of the complex processing at the BS which leads to a simplification of the mobile terminals. In this paper, we provide an overview of efficient linear and non-linear precoding techniques formulti-userMIMO systems. The performance of these techniques is assessed via simulations on statistical channelmodels, and on channels generated by the IlmProp, a geometry-based channel model that generates realistic correlations in space, time, and frequency.
Date : 2025-12-17 Size : 73kb User : ImranKhan