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Prior work in implementing spectrum sharing scenarios for cognitive radio networks has relied on the unlikely assumption of full cross-channel knowledge made available to the cognitive transmitter (CT) and/or the target primary receiver (PR). However, estimation of this cross-channel knowledge is not only important from a practical stand-point, but also in limiting the real interference power felt...
In this paper, we consider channel estimation for amplify-and-forward (AF) relay network with orthogonal frequency division multiplexing (OFDM) modulation. We propose a superimposed training strategy at relay that allows the destination node to obtain the separate channel information of the source-->relay link and the relay-->destination link. The proposed training strategy only requires two...
In this paper, we study the achievable rate of the training-based multi-input multi-output (MIMO) systems over time-varying flat fading channels modeled with the $L$-th order autoregressive, AR($L$), process. Using the Bayesian Cram\'{e}r-Rao lower bound (BCRB) to characterize the mean squared error of channel estimation, the achievable rate of the MIMO systems is investigated from the information-theoretical...
This paper examines the use of two-way training in multiple-input multiple-output (MIMO) wireless systems to discriminate the channel estimation (and, thus, data detection) performance between two receivers, namely, a legitimate receiver (LR) and an unauthorized receiver (UR). This work extends upon the discriminatory channel estimation (DCE) proposed in our prior work, where it was previously assumed...
Recently, in multi-antenna wireless systems, the use of artificial noise (AN) in training and data transmission phases has been respectively proposed to achieve performance discrimination between a legitimate receiver (LR) and an unauthorized receiver (UR). For data transmission, an AN-aided beamforming (ANBF) scheme has been proposed where the message is sent towards LR using beamforming while AN...
In this paper, we consider the problem of channel estimation for two-way relay networks (TWRN) under timeselective environment. We first parameterize the time-varying channels by the basis expansion model (BEM) and then propose a novel pilot symbol aided modulation (PSAM) for TWRN. A linear approach to estimate the cascaded channels is designed and the optimal training sequences are derived based...
We analyze the achievable diversity-multiplexing tradeoff (DMT) in MIMO fading channels with two-way channel training. We first consider a typical training scenario, where the transmitter transmits training symbols followed by data symbols, and the receiver performs channel estimation using the training symbols and then uses the imperfect channel estimates to decode the data symbols. It turns out...
This paper studies training-based transmissions over multiple-input multiple-output (MIMO) fading channels in the presence of jamming. Each transmission block consists of a training phase and a data transmission phase. From an information-theoretic viewpoint, we formulate a max-min problem on the energy allocation between the two phases. The legitimate user of the channel aims to design a robust energy...
For single-user MIMO channels with partial receiver CSI, we study the difference between inner and outer bounds of the mutual information achieved with Gaussian codebooks, as well as a related difference between capacity inner and outer bounds. In contrast to previous studies, we assume that the channel estimation error statistics are not given a priori, but depend on the parameters of a training...
Optimal training design and channel estimation for spatially correlated multi-user multi-input multi-output with orthogonal frequency-division multiplexing (MIMO-OFDM) systems is still an open research topic of great interest. This paper applies tractable semi-definite programming to obtain the optimal training signal for the general case of spatial channel correlations for multi-user MIMO-OFDM. The...
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