Time-Power-Frequency Hopping for D2D Discovery
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Solution Overview
Problem
In device-to-device (D2D) proximity discovery, existing technologies face challenges in effectively managing a large number of user equipment (UEs) at varying distances and power levels, leading to issues like overloading and masking of signals, particularly in open discovery scenarios where UEs need to detect multiple signals over a large range.
Innovation Solution
Implementing a time-power-frequency hopping scheme where UEs transmit and receive signals using non-contiguous sequences of time instances, power levels, and frequencies, assigned by the network to reduce overlapping resources and improve detection capabilities, using mechanisms like time hopping, power hopping, and frequency hopping to avoid collisions and ensure accurate signal detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If UEs transmit discovery signals using contiguous resources at fixed time instances and power levels, then the system is simple to implement, but signal overloading and masking occur in dense UE environments
Solution Approach 1:
The patent applies dynamics by making the resource allocation flexible and adaptive rather than fixed. UEs dynamically select time instances, power levels, and frequencies from assigned sequences based on hopping patterns, allowing the system to adapt to varying channel conditions and UE densities, thereby improving signal detection accuracy while managing complexity through structured randomness.
Solution Approach 2:
The patent introduces multiple dimensions for resource allocation: time hopping (different time instances), power hopping (different power levels), and frequency hopping (different frequencies). By expanding from a single-dimension resource allocation to multi-dimensional allocation, the system distributes signals across diverse resource spaces, reducing overloading and masking effects while maintaining manageable complexity through pattern-based assignment.
2Reliability
If UEs use fixed time instances and power levels for discovery signals, then resource assignment is simple, but near UEs overload far UEs causing detection failure
Solution Approach 1:
The patent applies local quality by assigning different local characteristics (time instances, power levels, frequencies) to different UEs within the same cell. Each UE receives a unique combination of hopping parameters, creating localized resource allocation that prevents uniform overloading. This allows far UEs to be detected by ensuring their signals do not consistently collide with near UE signals, while maintaining operational simplicity through network-configured patterns.
Solution Approach 2:
The network performs preliminary action by pre-configuring hopping sequences and patterns for UEs before discovery signal transmission. This advance assignment of diverse time-power-frequency combinations ensures that near and far UEs are differentiated in the resource domain before transmission occurs, preventing overloading issues while keeping UE operation simple through predetermined patterns.
3Measurement precision
If all UEs transmit discovery signals simultaneously on the same frequency, then frequency resources are efficiently utilized, but signal masking occurs reducing detection accuracy
Solution Approach 1:
The patent applies segmentation by dividing the frequency resource into multiple segments and assigning different segments to different UEs through frequency hopping patterns. Instead of all UEs using the same frequency simultaneously, the frequency domain is segmented and allocated dynamically, reducing signal masking while maintaining efficient frequency utilization through structured resource distribution.
Solution Approach 2:
The patent uses periodic action through time-varying frequency hopping patterns where UEs periodically change their assigned frequency resources. This periodic reassignment ensures that frequency resources are efficiently utilized over time while preventing persistent masking, as UEs transition through different frequency segments in a structured periodic manner.
Data Source
AI summary
A system and method for D2D discovery is provided. In an embodiment the method includes sending, by a base station, first parameters to a first User Equipment (UE) indicating a set of discovery resources in a discovery cycle, wherein the discovery cycle comprises a plurality of subframes; and sending, by the base station, second parameters to the first UE indicating a first probability for transmitting a first discovery signal to a second UE on a subframe of the plurality of subframes so that the first UE is capable of transmitting the first discovery signal to a second UE in the discovery cycle according to the first parameters when a random number between 0 and 1, selected by the first UE, is equal or larger than the first probability.