چكيده به لاتين
We introduce the Spatial Modulation (SM) as a new concept in Multiple Input–Multiple Output systems (MIMO). In this type of modulation, the modulated symbol and antenna index are jointly selected proportional to the transmitter data. SM has a lower computational complexity, hardware complexity, and power consumption compared to the spatial multiplexing. Thus, the SM is an ideal candidate for Massive MIMO systems in which Base Stations need Channel State Information to detect the signals transmitted from the users in uplink and to pre-code the signals in downlink. Then, in such systems channel estimation and channel estimation error play essential roles.
This thesis studies SM schemes in multi-cell multi-user Massive MIMO systems as a promising energy-efficient technique for the fifth generation (5G) wireless networks. Accordingly, the effect of channel estimation errors on the energy efficiency of Massive MIMO systems with SM is investigated and analyzed and a lower bound on the achievable rate of a user with matched filter detection is derived. In addition, in our simulations we consider some practical channel conditions, such as antenna correlation and pilot contamination. Analytical and simulations results show that the energy efficiency of such systems is more robust to channel estimation errors compared to the conventional Massive MIMO systems.
