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Register a new userAn Energy-Efficient Framework for the Analysis of MIMO Slow Fading Channels
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Added by
Vineeth Varma S
Publication date
2018
fields
Informatics Engineering
and research's language is
English
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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.
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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 from the analysis that the design of such rateless codes follows the design principle of approximately universal codes for parallel multiple-input multiple-output (MIMO) channels, in which each sub-channel is a MIMO channel. More specifically, it is shown that for a single-input single-output (SISO) channel, the previously developed permutation codes of unit length for parallel channels having rate LR can be transformed directly into rateless codes of length L having multiple rate levels (R, 2R, . . ., LR), to achieve the DMT performance limit.
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) divergence from the original matrix distribution. The utility of the results are demonstrated in a) computing the average capacity/rate expressions of $kappa-mu$/$eta-mu$ MIMO systems b) computing outage probability (OP) expressions for maximum ratio combining (MRC) for $kappa-mu$/$eta-mu$ faded MIMO channels c) ergodic rate expressions for zero-forcing (ZF) receiver in an uplink single cell massive MIMO scenario with low resolution analog-to-digital converters (ADCs) in the antennas. These approximate expressions are compared with Monte-Carlo simulations and a close match is observed.
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-RAN is adopted to mitigate the burden of front-haul and improve the end to end (E2E) latency. On other hand, virtualization and network function virtualization (NFV) are IT techniques that aim to convert the functions from hardware to software based functions. Many merits could be brought by the employment of NFV in mobile networks including a high degree of reliability, flexibility and energy efficiency. In this paper, a virtualization framework is introduced for F-RAN to improve the energy efficiency in 5G networks. In this framework, a gigabit passive optical network (GPON) is leveraged as a backbone network for the proposed F-RAN architecture where it connects several evolved nodes B (eNodeBs) via fibre cables. The energy-efficiency of the proposed F-RAN architecture has been investigated and compared with the conventional C-RAN architecture in two different scenarios using mixed integer linear programming (MILP) models. The MILP results indicate that on average a 30% power saving can be achieved by the F-RAN architecture compared with the C-RAN architecture.
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 incurred by the delay constraint. This paper introduces a notion of worst-case expected-capacity loss. Focusing on the slow-fading scenario (one-block delay), the worst-case additive and multiplicative expected-capacity losses are precisely characterized for the point-to-point fading channel. Extension to the problem of writing on fading paper is also considered, where both the ergodic capacity and the additive expected-capacity loss over one-block delay are characterized to within one bit per channel use.
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 an efficient way, integrating the data collection and fusion in one step by over-the-air computation (AirComp). Its shortcoming, however, is signal distortion when channel gains of nodes are different, which cannot be well solved by transmission power control alone in times of deep fading. To address this issue, in this paper, we propose a multi-slot over-the-air computation (MS-AirComp) framework for the sum estimation in fading channels. Compared with conventional data collection (one slot for each node) and AirComp (one slot for all nodes), MS-AirComp is an alternative policy that lies between them, exploiting multiple slots to improve channel gains so as to facilitate power control. Specifically, the transmissions are distributed over multiple slots and a threshold of channel gain is set for distributed transmission scheduling. Each node transmits its signal only once, in the slot when its channel gain first gets above the threshold, or in the last slot when its channel gain remains below the threshold. Theoretical analysis gives the closed-form of the computation error in fading channels, based on which the optimal parameters are found. Noticing that computation error tends to be reduced at the cost of more transmission power, a method is suggested to control the increase of transmission power. Simulations confirm that the proposed method can effectively reduce computation error, compared with state-of-the-art methods.
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