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Abstract
We consider a multi-point channel charting (CC)
based uplink pilot allocation algorithm for a multi-cell network.
We create the channel chart on an offline phase and map
the base station (BS) locations to charting locations. The chart
provides an approximation of the geometry of the network, with
imprecise but indicative distances and directions. Accordingly we
model the angle of arrival (AoA) of the signal arriving at the
BS from a user equipment (UE) on the CC by a probability
distribution. We make use of AoA distributions on the CC
to construct similarity weights between users; users nearby in
the angular domain have large similarity, whereas more distant
users have smaller similarity values. The points of view of
all BSs are considered to create a global similarity matrix. A
constrained weighted graph colouring algorithm is then applied
to allocate pilots. Simulation results show that the proposed pilot
allocation algorithm outperforms state of the art CC-based pilot
allocation algorithms. The performance of the CC-angle based
pilot allocation scheme is comparable to that obtained by using
known physical locations and angle spread information.
based uplink pilot allocation algorithm for a multi-cell network.
We create the channel chart on an offline phase and map
the base station (BS) locations to charting locations. The chart
provides an approximation of the geometry of the network, with
imprecise but indicative distances and directions. Accordingly we
model the angle of arrival (AoA) of the signal arriving at the
BS from a user equipment (UE) on the CC by a probability
distribution. We make use of AoA distributions on the CC
to construct similarity weights between users; users nearby in
the angular domain have large similarity, whereas more distant
users have smaller similarity values. The points of view of
all BSs are considered to create a global similarity matrix. A
constrained weighted graph colouring algorithm is then applied
to allocate pilots. Simulation results show that the proposed pilot
allocation algorithm outperforms state of the art CC-based pilot
allocation algorithms. The performance of the CC-angle based
pilot allocation scheme is comparable to that obtained by using
known physical locations and angle spread information.
| Original language | English |
|---|---|
| Title of host publication | 2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2024 |
| Publisher | IEEE |
| Pages | 166-170 |
| Number of pages | 5 |
| ISBN (Electronic) | 979-8-3503-9318-7 |
| DOIs | |
| Publication status | Published - 2024 |
| MoE publication type | A4 Conference publication |
| Event | IEEE International Workshop on Signal Processing Advances in Wireless Communications - Lucca, Italy Duration: 10 Sept 2024 → 13 Sept 2024 |
Publication series
| Name | SPAWC |
|---|---|
| ISSN (Electronic) | 1948-3252 |
Conference
| Conference | IEEE International Workshop on Signal Processing Advances in Wireless Communications |
|---|---|
| Country/Territory | Italy |
| City | Lucca |
| Period | 10/09/2024 → 13/09/2024 |
Keywords
- pilot allocation
- Multi-cell systems
- angle-of-arrival
- channel charting
- pilot interference
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CHASER: Channel Charting as a Service
Tirkkonen, O. (Principal investigator), Al-Tous, H. (Project Member) & Li, X. (Project Member)
01/11/2023 → 31/10/2026
Project: Academy of Finland: Other research funding
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RILREW: Reinforcement Learning for Real-time Wireless Scheduling and Edge Caching: Theory and Algorithm Design
Tirkkonen, O. (Principal investigator), Amidzade, M. (Project Member), Srinivasan, A. (Project Member), Singh, U. (Project Member), Shaikh, B. (Project Member), Al-Tous, H. (Project Member) & Li, X. (Project Member)
01/01/2022 → 31/12/2024
Project: Academy of Finland: Other research funding