Downlink virtual MIMO-NOMA (Multiple Input Multiple Output-Non-Orthogonal Multiple Output) method based on power and rate joint optimization

A MIMO-NOMA, joint optimization technology, applied in the field of wireless communication, to achieve the effect of reducing computational complexity, reducing system overhead, and ensuring cluster fairness

Active Publication Date: 2020-02-28
JINAN UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the implementation of virtual MIMO technology brings new challenges such as da

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  • Downlink virtual MIMO-NOMA (Multiple Input Multiple Output-Non-Orthogonal Multiple Output) method based on power and rate joint optimization
  • Downlink virtual MIMO-NOMA (Multiple Input Multiple Output-Non-Orthogonal Multiple Output) method based on power and rate joint optimization
  • Downlink virtual MIMO-NOMA (Multiple Input Multiple Output-Non-Orthogonal Multiple Output) method based on power and rate joint optimization

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Embodiment

[0058] For the convenience of describing this embodiment, the following symbols are first defined: bold uppercase and lowercase letters are used to represent matrix and vector respectively; X T 、X H 、X -1 and x 1 / 2 represent matrix transpose, conjugate transpose, matrix inverse and Hermitian square root, respectively; represents the Moore-Penrose pseudoinverse and vec, tr, det, and, and diag are operators for vectorization, trace, determinant, and diagonalization, respectively; [X] ij Indicates the (i, j)th element; 0 n and I n represent the all-zero vector and the identity matrix, respectively; respectively represent the set of m×n dimensional complex matrices; the symbols is the imaginary unit; E A Indicates the expectation operator in the random variable A; o(·) represents the little O notation; (·) n represents the Pochhammer symbol; ∪(·) represents the union; the symbol means "asymptotically equal to"; the symbol ∝ means "proportional to"; Γ(x) means the ga...

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Abstract

The invention discloses a downlink virtual MIMO-NOMA method based on power and rate joint optimization. The method comprises the following steps: firstly, enabling a terminal node to form a pluralityof virtual array antenna clusters through an ad hoc network protocol, and enabling each cluster to report path loss and channel statistical characteristics to a base station; then, a system average throughput maximization problem is constructed on a base station side, and an alternate iterative optimization algorithm is utilized to perform joint optimization of power and rate; next, the base station feeds back NOMA decoding sequence information to each cluster, and uses precoding and superposition coding technologies to perform power domain multiplexing on multiple data streams requested by each cluster; and finally, segmenting the data volume by utilizing zero-breaking detection, and decoding the expected signal by utilizing a continuous interference elimination technology. Compared withthe traditional OMA, NOMA and virtual MIMO technologies, the method has the advantages that the system capacity can be remarkably improved and the cluster fairness is ensured at a high signal-to-noiseratio.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to a downlink virtual MIMO-NOMA method based on joint optimization of power and rate. Background technique [0002] With the astonishing growth of Internet of Things (IoT) devices in 5G scenarios (e.g., smart cities, connected healthcare, industrial Internet, vehicle networks), a large number of wireless sensors are being deployed. Massive amounts of sensory data are collected sporadically and forwarded to the cloud via connected IoT devices, cellular networks, and the Internet. The Ericsson report has predicted that by 2024, the number of short-range and cellular IoT devices will reach 17.8 billion and 4.1 billion, respectively. In addition, Cisco also released its Visual Networking Index (VNI) forecast, which predicts that machine-to-machine (M2M) type connections in IoT networks will grow from 6.1 billion in 2017 to 14.6 billion in 2022. The proliferation of IoT ...

Claims

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Application Information

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IPC IPC(8): H04B7/0426H04B7/0413H04W52/14H04W52/26H04W72/04H04W72/08
CPCH04B7/0426H04B7/0413H04W52/143H04W52/267H04W72/0473H04W72/542
Inventor 施政杨光华塞奥佐罗斯·特斯菲斯马少丹屈挺
Owner JINAN UNIVERSITY
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