This correspondence deals with the construction of minimum Euclidean distance precoders for multiple-input multiple-output (MIMO) systems with up to four transmit antennas. By making use of a state-of-the-art technique for optimization over the unitary group, we can numerically optimize the MIMO precoders. The correspondence then proceeds by identifying the obtained precoders as well-known lattices (square Z2, Schl"afli D4, D6, Gosset E8). With three

In this work, we develop an anchor-less relative localisation algorithm aimed to be used in multi-robot teams. The localisation is performed based on the Received Signal Strength Indicator (RSSI) readings collected from the messages exchanged between nodes. We use the RSSI as a rough estimate of the inverse of distance between any pair of communicating nodes, and we claim that such estimates provide a coarse information of the nodes relative localisation

In this paper, we propose a new two-way time synchronization (TS) method for OFDM-based wireless systems. It relies on the time-reversal (TR) technique in order to remove the effect of the channel phase after the signal round-trip. For this reason, the method is named TR-TS. TR technique yields a linear phase rotation across subcarriers, regardless whether the channel is minimum, maximum, or mixed phase. This phase is proportional to the difference

In this paper we address the problem of blind recovery of multiple OFDM data streams in a Multiple-Input Multiple-Output (MIMO) system. We propose an equalization algorithm which is based on a combined criterion designed to cancel both intersymbol interference (ISI) and co-channel interference (CCI). ISI is minimized by using a modified Vector Constant Modulus criterion while CCI is minimized by a decorrelation criterion. We establish conditions

In this paper we introduce a Riemannian algorithm for minimizing (or maximizing) a real-valued function {mathcal J} of complex-valued matrix argument {mathbf W} under the constraint that {mathbf W} is an n×n unitary matrix. This type of constrained optimization problem arises in many array and multi-channel signal processing applications. We propose a conjugate gradient (CG) algorithm on the Lie group of unitary matrices $U(n)$. The algorithm fully

In many engineering applications we deal with constrained optimization problems with respect to complex-valued matrices. This paper proposes a Riemannian geometry approach for optimization of a real-valued cost function {mathcal J} of complex-valued matrix argument {mathbf W}, under the constraint that {mathbf W} is an $n times n$ unitary matrix. We derive steepest descent (SD) algorithms on the Lie group of unitary matrices $U(n)$. The proposed