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The problem of blind channel estimation under space-time block coded (STBC) transmissions is addressed. Firstly, a blind channel estimation criterion that generalizes previous works is proposed. The technique is solely based on second-order statistics (SOS) and if the channel is identifiable, the estimate is obtained as the main eigenvector of a generalized eigenvalue problem (GEV). Secondly, a new transmission technique is proposed to solve the indeterminacies associated to the blind channel estimation problem. The technique is based on the combination of different STBCs, and it can be reduced to a nonredundant precoding consisting in the rotation or permutation of the transmit antennas. Unlike other previous approaches, the proposed technique does not imply a penalty in the transmission rate or capacity of the STBC system, while it is able to avoid the ambiguities in many practical cases, which is illustrated by means of some simulation examples.

We analyze the performance of SNR-based scheduling algorithms in broadcast ergodic fading channels where multiuser selection diversity is exploited. At each channel state, the user with the highest weighted signal-to-noise ratio is selected to be transmitted. The use of weights associated to the users allows us to control the degree of fairness among users and to arrange them according to a prescribed quality of service. These weights parametrize the scheduling algorithms so each set of weights corresponds to a specific scheduling algorithm. Assuming Rayleigh fading broadcast channel, we derive a closed-form expression for the achievable user's rates as a function of the scheduling algorithm, the channel fading statistics of each user, and the transmit power. With the help of this expression, we solve some interesting inverse problems. For example, for a given arbitrary channel statistics we obtain the optimum scheduling algorithm to achieve a prescribed set of users' rates with minimum transmit power.

This paper treats the identification of nonlinear systems that consist of a cascade of a linear channel and a nonlinearity, such as the well-known Wiener and Hammerstein systems. In particular, we follow a supervised identification approach that simultaneously identifies both parts of the nonlinear system. Given the correct restrictions on the identification problem, we show how kernel canonical correlation analysis (KCCA) emerges as the logical solution to this problem. We then extend the proposed identification algorithm to an adaptive version allowing to deal with time-varying systems. In order to avoid overfitting problems, we discuss and compare three possible regularization techniques for both the batch and the adaptive versions of the proposed algorithm. Simulations are included to demonstrate the effectiveness of the presented algorithm.

Abstract In this paper, we present an experimental evaluation of the performance benefits provided by flexible duplexing, an access technique that allows uplink and downlink cells to coexist within the same time-frequency resource blocks. In order to replicate a wireless multi-tier network composed of 1 macro-cell and 2 small cells, a measurement campaign has been conducted using an indoor wireless testbed comprised of a total of 6 multiple-input multiple-output (MIMO) software-defined radio (SDR) devices. Since each cell has a single active user, each uplink/downlink configuration can be identified with a different interference channel, over which interference alignment (IA) is used as an inter-cell interference management technique and compared to other existing methods. The obtained results show that flexible duplexing clearly outperforms the conventional time-division duplex (TDD) access approach, where all cells operate synchronized either in uplink or dowlink mode. Additionally, interference alignment consistently provides better results in most of the interference regimes when compared to minimum mean square error (MMSE)-based schemes. The impact of channel estimate quality on the different communication strategies is also studied. It is worth highlighting that the presented over-the-air (OTA) experiments represent the first implementation of IA with real-time precoding and decoding.