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In this work, a new energy-efficiency performance metric is proposed for MIMO (multiple input multiple output) point-to-point systems. In contrast with related works on energy-efficiency, this metric translates the effects of using finite blocks for transmitting, using channel estimates at the transmitter and receiver, and considering the total power consumed by the transmitter instead of the radiated power only. The main objective pursued is to choose the best pre-coding matrix used at the transmitter in the following two scenarios~: 1) the one where imperfect channel state information (CSI) is available at the transmitter and receiver~; 2) the one where no CSI is available at the transmitter. In both scenarios, the problem of optimally tuning the total used power is shown to be non-trivial. In scenario 2), the optimal fraction of training time can be characterized by a simple equation. These results and others provided in the paper, along with the provided numerical analysis, show that the present work can therefore be used as a good basis for studying power control and resource allocation in energy-efficient multiuser networks.
In this paper the performance limits and design principles of rateless codes over fading channels are studied. The diversity-multiplexing tradeoff (DMT) is used to analyze the system performance for all possible transmission rates. It is revealed fro
Approximate random matrix models for $kappa-mu$ and $eta-mu$ faded multiple input multiple output (MIMO) communication channels are derived in terms of a complex Wishart matrix. The proposed approximation has the least Kullback-Leibler (KL) divergenc
Fog radio access network (F-RAN) and virtualisation are promising technologies for 5G networks. In F-RAN, the fog and cloud computing are integrated where the conventional C-RAN functions are diverged to the edge devices of radio access networks. F-R
For delay-limited communication over block-fading channels, the difference between the ergodic capacity and the maximum achievable expected rate for coding over a finite number of coherent blocks represents a fundamental measure of the penalty incurr
IoT systems typically involve separate data collection and processing, and the former faces the scalability issue when the number of nodes increases. For some tasks, only the result of data fusion is needed. Then, the whole process can be realized in