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A especially favorable multiple-input multiple-output (MIMO)-based concept for future mobile radio systems consists of the application of joint detection (JD) in the uplink and joint transmission (JT) in the downlink. By this, all the computational complex signal processing is shifted to the base station (BS), resulting in low-complexity mobile stations. Both JD and JT require channel knowledge at the BS which, if time-division duplexing is applied, can be obtained by training signal-based channel estimation in the uplink. Unfortunately, channel estimates are never perfect, which leads to performance degradations if these channel estimates, instead of perfect channel knowledge, are used for JD or JT. Especially channel errors due to the time variance of the mobile radio channel are often considered to be a severe problem in the application of MIMO techniques in high-mobility scenarios, which requires closer investigation. In this paper, a novel analysis of the performance degradations of zero-forcing JD and JT due to imperfect channel knowledge is presented. The analysis is based on linear Taylor approximation of the data-estimation error due to imperfect channel knowledge.