Distributed Antenna Mobility Using Compressive Sampling Handover
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Solution Overview
Problem
Existing wireless communication systems face challenges in managing communications of moving mobile devices, particularly when they cross Routing Areas, leading to abrupt transitions and increased signaling delays, as the network loses track of the user equipment until a RACH transmission is made, resulting in inefficient resource allocation and reduced throughput.
Innovation Solution
A compressive sampling approach is implemented, where user equipment (UE) senses and detects wireless transmissions using remote samplers, and a Central Brain processes these signals to estimate communication parameters, allowing for seamless transitions between communication regions by reusing pilot signals and optimizing resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mobile stations monitor downlink channels and perform RACH transmission when crossing Routing Areas, then the network can re-establish track of user equipment, but abrupt transitions and signaling delays occur resulting in inefficient resource allocation
Solution Approach 1:
The system performs preliminary actions by having the network predict future positions of mobile stations based on current mobility patterns and prepare communication resources in advance. When a mobile station enters a prediction zone, the network has already allocated resources and established connection parameters, eliminating the need for abrupt RACH transmissions and handshaking sequences that cause signaling delays.
2Reliability
If mobile stations perform handshaking sequences to identify themselves, then the network can re-establish communication, but abrupt hard handoff events occur reducing communication efficiency
Solution Approach 1:
The network performs preliminary actions by predicting mobile station trajectories and pre-establishing communication parameters before the mobile station actually crosses boundary areas. This eliminates the need for abrupt hard handoff events and repeated handshaking sequences, as connection parameters are already prepared and available, maintaining continuous communication efficiency.
Solution Approach 2:
The system dynamically adjusts communication parameters based on real-time mobility patterns. Instead of static routing areas requiring abrupt handoffs, the prediction zones and communication parameters are dynamically adapted to the mobile station's movement, enabling seamless transitions that maintain communication efficiency while ensuring reliable re-establishment.
Data Source
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Figure 1B
Figure 1C
AI summary
A device, method or system implements operations to receive compressed samples of wireless transmissions from a plurality of user equipment (UEs) traveling through different communication regions in a wireless network, and detect information in the wireless transmissions of the UEs based on the compressed samples.