Holger Boche

We address the problem of joint downlink beamforming in a power-controlled network, where independent data streams are to be transmitted from a multiantenna base station to several decentralized single-antenna terminals. The total transmit power is limited and channel information (possibly statistical) is available at the transmitter. The design goal: jointly adjust the beamformers and transmission powers according to individual SINR requirements. In this context, there are two closely related optimization problems. P1: maximize the jointly achievable SINR margin under a total power constraint. P2: minimize the total transmission power while satisfying a set of SINR constraints. In this paper, both problems are solved within a unified analytical framework. Problem P1 is solved by minimizing the maximal eigenvalue of an extended crosstalk matrix. The solution provides a necessary and sufficient condition for the feasibility of the SINR requirements. Problem P2 is a variation of problem P1. An important step in our analysis is to show that the global optimum of the downlink beamforming problem is equivalently obtained from solving a dual uplink problem, which has an easier-to-handle analytical structure. Then, we make use of the special structure of the extended crosstalk matrix to develop a rapidly converging iterative algorithm. The optimality and global convergence of the algorithm is proven and stopping criteria are given.

In a three-node network bidirectional communication between two nodes can be enabled by a half-duplex relay node with a decode-and-forward protocol. In the first phase, the messages of two nodes are transmitted to the relay node. In the second phase a re-encoded composition is broadcasted by the relay node. In this work the capacity region of the broadcast phase in terms of the maximal probability of error is determined. It is characterized by the mutual informations of the separate channels coupled by the common input.

We study the optimal transmission strategy of a single-user multiple-input/multiple-output communication system with covariance feedback. We consider the situation with correlated receive and correlated transmit antennas in Rayleigh flat fading. Furthermore, we assume that the receiver has perfect channel state information, while the transmitter knows only the transmit correlation matrix and the receive correlation matrix. We show that transmitting in the direction of the eigenvectors of the transmit correlation matrix is the optimal transmission strategy. In addition to this, the optimal power allocation is studied and a necessary and sufficient condition for optimality of beamforming is derived. All theoretical results are illustrated by numerical simulations.

Energy efficiency matters in future mobile communications networks. The key driving factor is the growing energy cost of network operations that can make up as much as 50% of the total operational cost today [1]. In the context of green information and communication technology (ICT), this has led to many global initiatives such as the Green Touch consortium.

We address the problem of minimum mean square error (MMSE) transceiver design for point-to-multipoint transmission in multiuser multiple-input-multiple-output (MIMO) systems. We focus on the problem of minimizing the downlink sum-MSE under a sum power constraint. It is shown that this problem can be solved efficiently by exploiting a duality between the downlink and uplink MSE feasible regions. We propose two different optimization frameworks for downlink MMSE transceiver design. The first one solves an equivalent uplink problem, then the result is transferred to the original downlink problem. Duality ensures that any uplink MMSE scheme, e.g., linear MMSE reception or MMSE-decision feedback equalization (DFE), has a downlink counterpart. We propose two globally optimum algorithms based on convex optimization. The basic idea of the second framework is to perform optimization in an alternating manner by switching between the virtual uplink and downlink channels. This strategy exploits that the same MSE can be achieved in both links for a given choice of transmit and receive filters. This iteration is proven to be convergent.