Interference is known as a major obstacle for the spectral efficiency increase promised by multiple-antenna techniques in cellular wireless communications. Recently, it has been shown that multi-cell coordination can mitigate interference and improve system performance dramatically. Hence, we concentrate on the downlink of multi-cell multiple-antenna (at both ends) wireless networks also known as network multiple-input multiple-output (MIMO) or coordinated multi-point (CoMP) transmission/reception systems. In multi-cell coordination, antennas from multiple base stations form a large MIMO system. Consequently, coordination comes with high signal processing overhead. In this dissertation we focus on reduced-complexity transmission and reception strategies in partially coordinated multi-cell systems, where the user data are partially shared between base stations. We first model partial coordination using MIMO interference channel with generalized linear constraints. Then, we investigate linear transmission strategies using this channel model. The contributions of this dissertation fall into the following categories of techniques: (i) Block diagonalization (multiple-antenna multi-user zero-forcing) transmit precoding under individual power constraints. (ii) Minimum mean square error (MMSE) linear precoding and equalization design; (iii) Worst-case robust precoding and equalization, where we consider imperfect channel state information available at the transmitter and receiver. Furthermore, our simulation setup accounts for realistic cellular parameters in evaluating the performance in multi-cell networks.
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