Predictive Relay Selection for mmWave Beamforming
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Solution Overview
Problem
Millimeter wave (mmWave) communications in urban settings face challenges due to signal blockage and severe signal attenuation, which existing relay-assisted beamforming techniques struggle to address effectively, leading to network latency and quality-of-service (QoS) issues.
Innovation Solution
The implementation of a resource-efficient relay selection scheme that uses predictive and distributed methods to optimize relay-assisted beamforming in 2-hop Amplify-and-Forward (AF) cooperative networks, leveraging channel correlations to reduce latency and CSI estimation overhead, and employing static relays deployed in clusters to enhance QoS by selecting representative relays based on maximized minimum mean square error (MMSE) predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If relay-assisted beamforming is used to mitigate signal blockage and attenuation, then communication range and QoS are improved, but network latency and CSI estimation overhead increase
Solution Approach 1:
The patent performs relay selection in advance for the next time slot during the current time slot, using predictive MMSE estimation of future SINR. This preliminary action allows the selected relay to be ready before needed, eliminating selection latency during actual transmission and reducing overall network latency while maintaining QoS.
Solution Approach 2:
The patent divides relay selection into separate time slots: current slot t for beamforming with currently selected relay, and predictive selection for next slot t+1. This segmentation allows parallel processing of beamforming and relay selection, reducing time overhead and latency.
2Reliability
If relay selection is performed to optimize beamforming, then QoS is improved, but resource demand and network latency increase
Solution Approach 1:
Relay selection is performed in advance during time slot t for use in time slot t+1, using predictive MMSE estimation. This preliminary action eliminates the need for resource-intensive real-time selection during transmission, reducing both resource demand and latency while maintaining optimal QoS.
Solution Approach 2:
The system uses feedback from current CSI measurements to predict future SINR and select relays optimally. This feedback mechanism enables intelligent relay selection that improves QoS without requiring exhaustive resource exploration, as the selection is guided by predictive estimation based on observed channel conditions.
3Area of stationary object
If dense network of base stations is deployed to optimize LoS coverage, then coverage area is improved, but interference between transmissions increases
Solution Approach 1:
The patent implements distributed relay-assisted beamforming where each relay cluster operates semi-independently with local CSI estimation and predictive relay selection. This local quality approach allows dense deployment for coverage while minimizing inter-cluster interference through spatial diversity and localized beamforming operations.
Solution Approach 2:
Relays act as intermediaries between base stations and end users, enabling distributed beamforming that extends LoS coverage while managing interference. The relays perform local signal processing and forwarding, which reduces direct interference between base stations while maintaining comprehensive coverage through cooperative beamforming.
Data Source
AI summary
Systems, methods, architectures, mechanisms and apparatus for relay beamforming of mmWave communications in an environment having signal blockage and signal attenuation challenges, such as found in an urban setting support distributed, relay-assisted beamforming mechanisms that exploit the spatial diversity of mmWave signal propagation, including a resource efficient relay selection scheme designed to optimally enhance QoS in 2-hop Amplify-and-Forward (AF) cooperative networks. Relay selection is implemented in a predictive and distributed manner.