Browsing by Author "Khan, Muhammad Bilal"

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Channel Charting Based Pilot Allocation in MIMO Systems
(2025-01-01) Shaikh, Bushra; Garau Burguera, Pere; Al-Tous, Hanan; Juntti, Markku; Khan, Muhammad Bilal; Tirkkonen, Olav
A4 Artikkeli konferenssijulkaisussa
We consider uplink pilot allocation based on multipoint channel charting (CC) to mitigate pilot contamination in a multi-cell network with spatially correlated MIMO channels. The channel chart is created in an offline phase with full information, i.e. user channel covariance matrices are estimated at multiple base stations (BSs). In the online phase, we assume that only partial information about a user’s channel covariance is known, i.e., it is available only at the serving BS. A machine learning framework is developed to predict the CC locations in the online phase. Pilots are allocated to active users in the online phase based on weighted graph colouring. CC locations are used as proxies of user locations; similarity weights between users are constructed from CC distances. Simulation results show that the CC based approach with partial information in the online phase outperforms a solution based on full angle-ofarrival information, and performs closely to an algorithm with full covariance information. We also consider a partial information machine learning framework to predict the channel covariance matrices at other BSs, which slightly outperforms CC based approach, with the price of a
Pilot Assignment based on AoA Information using Channel Charting in Massive MIMO Systems
(2024) Shaikh, Bushra; Garau Burguera, Pere; Al-Tous, Hanan; Juntti, Markku J.; Khan, Muhammad Bilal; Tirkkonen, Olav
A4 Artikkeli konferenssijulkaisussa
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.