Elisabeth de Carvalho

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We pursue our Iterative Quadratic Maximum Likelihood IQML approach to blind estimation of multiple FIR channels. We use a parameterization of the noise subspace in terms of linear prediction quantities. This parameteriza-tion is robust w.r.t. a channel length mismatch. Specifically , when the channel length is overestimated, no problems occur.(More)
—We introduce a new two–step relaying scheme based on superposition coding, SC–relaying. In Step 1, the source AS broadcasts a message, created by superposition coding, to the relay AR and the destination AD. After decoding the information from AS, AR relays a part of this message in Step 2, by using a codebook that is adapted to the link AR − AD. The(More)
— This paper investigates the problem of blindly and semi–blindly acquiring the channel gains for an underdetermined synchronous multiuser multicarrier system. The special case of a MISO (Multiple Input Single Output) channel is considered where the different users transmit at the same time and in the same bandwidth. In order to separate the different users(More)
—Wireless networks with many antennas at the base stations and multiplexing of many users, known as Massive MIMO systems, are key to handle the rapid growth of data traffic. As the number of users increases, the random access in contemporary networks will be flooded by user collisions. In this paper, we propose a reengineered random access protocol, coined(More)
—The Massive MIMO (multiple-input multiple-output) technology has great potential to manage the rapid growth of wireless data traffic. Massive MIMO achieves tremendous spectral efficiency by spatial multiplexing of many tens of user equipments (UEs). These gains are only achieved in practice if many more UEs can connect efficiently to the network than(More)
We explore the identifiability conditions for blind and semi-blind multiuser multichannel identification. Starting with the determin-istic approach, we compare the identifiability conditions on the channel and the sources of training sequence based channel identification , blind and semi-blind channel identification. Further on, we use the stochastic(More)
—This paper studies various cooperative diversity schemes for Orthogonal Frequency Division Multiple Access (OFDMA)-Time Division Duplex (TDD) based two-hop cellular networks in low mobility scenarios, where the instantaneous channel state information is available at the base station. A user scheduling and radio resource allocation technique is developed in(More)
We present t w o approaches to stochastic Maximum Likelihood identication of multiple FIR channels, where the input symbols are assumed Gaussian and the channel de-terministic. These methods allow semi-blind identication, as they accommodate a priori knowledge in the form of a (short) training sequence and appears to be more relevant in practice than purely(More)