Large scale datasets for THz based midhaul link evaluation between CU and DU

In this paper, we investigate the feasibility of THz
wirelessmidhaullinksbetweentheCentralUnits(CU)and
Distributed Units (DU) in a disaggregated network architectureIn this paper, we investigate the feasibility of THz

wireless midhaul links between the Central Units (CU) and
Distributed Units (DU) in a disaggregated network architecture
with functional splits. We consider the network planning problem
to examine the impacts of the number of deployed CUs and power
allocations at each CU on the system performance measured
in terms of the achieved data rates on the wireless midhaul

In this paper, we investigate the feasibility of THz

wireless midhaul links between the Central Units (CU) andIn this paper, we investigate the feasibility of THz
wireless midhaul links between the Central Units (CU) and
Distributed Units (DU) in a disaggregated network architecture
with functional splits. We consider the network planning problem
to examine the impacts of the number of deployed CUs and power
allocations at each CU on the system performance measured
in terms of the achieved data rates on the wireless midhaul
links between the CUs and DUs. To approach this problem, we
cast our system model as an instance of Multi-user Multiple
Input Multiple Output (MU-MIMO), and investigate an approach
based on signal-to-leakage noise ratio (SLNR) for efficient com-
putation of the transmit precoding vectors. Furthermore, we
explore different power allocation strategies to improve overall
performance when the transmit power at a CU is limited. The
impact of each of the network design parameters (i.e. number
of deployed CUs and power allocation) is investigated through
extensive simulation results. To this end, we have used ray-tracing
to establish an emulation framework for generating large-scale
datasets to model THz signal propagation.Distributed Units (DU) in a disaggregated network architecture
with functional splits. We consider the network planning problem
to examine the impacts of the number of deployed CUs and power
allocations at each CU on the system performance measured
in terms of the achieved data rates on the wireless midhaul
links between the CUs and DUs. To approach this problem, we
cast our system model as an instance of Multi-user Multiple
Input Multiple Output (MU-MIMO), and investigate an approach
based on signal-to-leakage noise ratio (SLNR) for efficient com-
putation of the transmit precoding vectors. Furthermore, we
explore different power allocation strategies to improve overall
performance when the transmit power at a CU is limited. The
impact of each of the network design parameters (i.e. number
of deployed CUs and power allocation) is investigated through
extensive simulation results. To this end, we have used ray-tracing
to establish an emulation framework for generating large-scale
datasets to model THz signal propagationlinks between the CUs and DUs. To approach this problem, we
cast our system model as an instance of Multi-user Multiple
Input Multiple Output (MU-MIMO), and investigate an approach
based on signal-to-leakage noise ratio (SLNR) for efficient com-
putation of the transmit precoding vectors. Furthermore, we
explore different power allocation strategies to improve overall
performance when the transmit power at a CU is limited. The
impact of each of the network design parameters (i.e. number
of deployed CUs and power allocation) is investigated through
extensive simulation results. To this end, we have used ray-tracing
to establish an emulation framework for generating large-scale
datasets to model THz signal propagationwith functional splits. We consider the network planning problemto examine the impacts of the number of deployed CUs and power
allocations at each CU on the system performance measured
in terms of the achieved data rates on the wireless midhaul
links between the CUs and DUs. To approach this problem, we
cast our system model as an instance of Multi-user Multiple
Input Multiple Output (MU-MIMO), and investigate an approach
based on signal-to-leakage noise ratio (SLNR) for efficient com-
putation of the transmit precoding vectors. Furthermore, we
explore different power allocation strategies to improve overall
performance when the transmit power at a CU is limited. The
impact of each of the In this paper, we investigate the feasibility of THz
wirelessmidhaullinksbetweentheCentralUnits(CU)andThis Dataset is used to evaluate THz based midhaul links. Towards Efficient THz-Based Wireless Midhaul

Links for 6G Transport NetworksDistributed Units (DU) in a disaggregated network architecture
with functional splits. We consider the network planning problem
to examine the impacts of the number of deployed CUs and power
allocations at each CU on the system performance measured
in terms of the achieved data rates on the wireless midhaul
links between the CUs and DUs. To approach this problem, we
cast our system model as an instance of Multi-user Multiple
Input Multiple Output (MU-MIMO), and investigate an approach
based on signal-to-leakage noise ratio (SLNR) for efficient com-
putation of the transmit precoding vectors. Furthermore, we
explore different power allocation strategies to improve overall
performance when the transmit power at a CU is limited. The
impact of each of the network design parameters (i.e. number
of deployed CUs and power allocation) is investigated through
extensive simulation results. To this end, we have used ray-tracing
to establish an emulation framework for generating large-scale
datasets to model THz signal propagationnetwork design parameters (i.e. number
of deployed CUs and power allocation) is investigated through
extensive simulation results. To this end, we have used ray-tracing
to establish an emulation framework for generating large-scale
datasets to model THz signal propagation