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In conventional Multiple-Input Multiple Output (MIMO) systems, each antenna requires its own Radio Frequency (RF) chain. Since each RF-chain includes several active components that have to be synchronised, costs and complexity become restrictive. The outphasing MIMO and the outphasing precoder architectures are possible approaches to mitigate this problem. The core of both architectures are Outphasing Elements (OEs), which are used to form a electronically controllable, passive antenna feed network. These OEs are analysed with respect to component tolerances.

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In this paper we study the spectral efficiency (SE) of a point-to-point massive multiple-input multiple-output system (P2P-massive MIMO) with limited radio frequency (RF) chains, i.e., analog-to-digital/ digital-to-analog (D2A/A2D) modules, at the transceivers. The resulting architecture is known as hybrid beamforming, where the joint analog and digital beamforming optimization maximizes the SE. We analyze the SE of the system by keeping the number of RF-chains low, but placing analog amplifiers at different paths.

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In this paper, we investigate the interference exploitation precoding for multi-level modulations in the downlink multi-antenna systems. We mathematically derive the optimal precoding structures based on the Karush-Kuhn-Tucker (KKT) conditions. Furthermore, by formulating the dual problem, the precoding problem for multi-level modulations can be transformed into a pre-scaling operation using quadratic programming (QP) optimization.

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This work considers a design of network in which multiple transmission points (TPs) cooperatively serve users by jointly precoding shared data. Considered problem formulation jointly designs the beamformers and performs TP-UE link selection, which aims in improving overall system rate. Proposed distributed Augmented ADMM algorithm features parallelization among TPs, which has practical importance for computational load distribution and reducing signaling overhead in backhaul.

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This work considers a design of network in which multiple transmission points (TPs) cooperatively serve users by jointly precoding shared data. Considered problem formulation jointly designs the beamformers and performs TP-UE link selection, which aims in improving overall system rate. Proposed distributed Augmented ADMM algorithm features parallelization among TPs, which has practical importance for computational load distribution and reducing signaling overhead in backhaul. This approach is different from others

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The emerging Internet of Things (IoT) has several salient characteristics that differentiate it from existing wireless networking architectures. These include the deployment of very large numbers of (possibly) low-complexity terminals; the need for low-latency, short-packet communications (e.g., to support automation); light or no infrastructure; and primary applications of data gathering, inference and control.

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Satellite systems might become an important supplement to 5G systems. In addition, compared with regular TCP, multipath TCP (MPTCP) provides a robust solution. However, due to the high latency and high loss of satellite networks, most of the existing multipath TCP congestion control schemes do not perform well. Therefore, we proposed a bandwidth and round-trip time detection-based congestion control (BWRD) for multipath TCP over highly lossy satellite networks. Simulations are running to evaluate the proposed BWRD algorithm.

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