Multiantenna Cellular Communications : Channel Estimation, Feedback, and Resource Allocation

The use of multiple antennas at base stations and user devices is a key component in the design of cellular communication systems that can meet the capacity demands of tomorrow. The downlink transmission from base stations to users is particularly limiting, both from a theoretical and a practical perspective, since user devices should be simple and power-efficient, and because many applications primarily create downlink traffic (e.g., video streaming). The potential gain of employing multiple antennas for downlink transmission is well recognized: the total data throughput increases linearly with the number of transmit antennas if the spatial dimension is exploited for simultaneous transmission to multiple users. In the design of practical cellular systems, the actual benefit of multiuser multiantenna transmission is limited by a variety of factors, including acquisition and accuracy of channel information, transmit power, channel conditions, cell density, user mobility, computational complexity, and the level of cooperation between base stations in the transmission design. The thesis considers three main components of downlink communications: 1) estimation of current channel conditions using training signaling; 2) efficient feedback of channel estimates; and 3) allocation of transmit resources (e.g., power, time and spatial dimensions) to users. In each area, the thesis seeks to provide a greater understanding of the interplay between different system properties. This is achieved by generalizing the underlying assumptions in prior work and providing both extensions of previous outcomes and entirely new mathematical results, along with supporting numerical examples. Some of the main thesis contributions can be summarized as follows. A framework is proposed for estimation of different channel quantities using a common optimized training sequence. Furthermore, it is proved that each user should only be allocated one data stream and utilize its antennas for receive combining and interference rejection, instead of using the antennas for reception of multiple data streams. This fundamental result is proved under both exact channel acquisition and under imperfections from channel estimation and limited feedback. This also has positive implications on the hardware and system design. Next, a general mathematical model is proposed for joint analysis of cellular systems with different levels of base station cooperation. The optimal multicell resource allocation can in general only be found with exponential computational complexity, but a systematic algorithm is proposed to find the optimal solution for the purpose of offline benchmarking. A parametrization of the optimal solution is also derived, creating a foundation for heuristic low-complexity algorithms that can provide close-to-optimal performance. This is exemplified by proposing centralized and distributed multicell transmission strategies and by evaluating these using multicell channel measurements.