Future wireless networks will be characterized by high network density and high communication frequencies. In such a scenario, this paper studies the resource allocation problem in Integrated Access and Backhaul networks operating at Terahertz (THz) that is a largely unexplored area. Resource sharing requires an efficient allocation strategy that is investigated here taking into account the re-irradiation phenomenon caused by molecular absorption characterizing THz communications. This effect induces spatial diversity that can be exploited through MIMO systems. The paper proposes a two-step allocation strategy aiming at maximizing the user sum rate: (i) first THz sub-bands are split between backhaul and aggregated access links, and then (ii) every IAB node allocates portions of its sub-bands to its associated UEs to satisfy their minimum rate targets. Step (i) is formulated as a combinatorial optimization problem and solved via a Genetic Algorithm, achieving near-optimal performance with significantly lower complexity than other solutions.

Spectrum Allocation for Terahertz-Based Integrated Access and Backhaul / Andrea Tani; Dania Marabissi. - ELETTRONICO. - (2025), pp. 1-6. ( European Wireless).

Spectrum Allocation for Terahertz-Based Integrated Access and Backhaul

Andrea Tani
;
Dania Marabissi
2025

Abstract

Future wireless networks will be characterized by high network density and high communication frequencies. In such a scenario, this paper studies the resource allocation problem in Integrated Access and Backhaul networks operating at Terahertz (THz) that is a largely unexplored area. Resource sharing requires an efficient allocation strategy that is investigated here taking into account the re-irradiation phenomenon caused by molecular absorption characterizing THz communications. This effect induces spatial diversity that can be exploited through MIMO systems. The paper proposes a two-step allocation strategy aiming at maximizing the user sum rate: (i) first THz sub-bands are split between backhaul and aggregated access links, and then (ii) every IAB node allocates portions of its sub-bands to its associated UEs to satisfy their minimum rate targets. Step (i) is formulated as a combinatorial optimization problem and solved via a Genetic Algorithm, achieving near-optimal performance with significantly lower complexity than other solutions.
2025
European Wireless Conference, EW 2025
European Wireless
Andrea Tani; Dania Marabissi
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1437195
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