Molecular Absorption-Aware User Assignment, Spectrum, and Power Allocation in Dense THz Networks with Multi-Connectivity

This paper develops a unified framework to maximize the network sum-rate in a multi-user, multi-BS downlink terahertz (THz) network by optimizing user associations, number and bandwidth of sub-bands in a THz transmission window (TW), bandwidth of leading and trailing edge-bands in a TW, sub-band assignment, and power allocations. The proposed framework incorporates multi-connectivity and captures the impact of molecular absorption coefficient variations in a TW, beam-squint, molecular absorption noise, and link blockages. To make the problem tractable, we first propose a convex approximation of the molecular absorption coefficient using curve fitting in a TW, determine the feasible bandwidths of the leading and trailing edge-bands, and then derive closed-form optimal solution for the number of sub-bands considering beam-squint constraints. We then decompose joint user associations, sub-band assignment, and power allocation problem into two sub-problems, i.e., \textbf{(i)} joint user association and sub-band assignment, and \textbf{(ii)} power allocation. To solve the former problem, we analytically prove the unimodularity of the constraint matrix which enables us to relax the integer constraint without loss of optimality. To solve power allocation sub-problem, a fractional programming (FP)-based centralized solution as well as an alternating direction method of multipliers (ADMM)-based light-weight distributed solution is proposed. The overall problem is then solved using alternating optimization until convergence. Complexity analysis of the algorithms and numerical convergence are presented. Numerical findings validate the effectiveness of the proposed algorithms and extract useful insights about the interplay of the density of base stations (BSs), Average order of multi-connectivity (AOM), molecular absorption, {hardware impairment}, {imperfect CSI}, and link blockages.

A Tractable Handoff-aware Rate Outage Approximation with Applications to THz-enabled Vehicular Network Optimization

In this paper, we first develop a tractable mathematical model of the handoff (HO)-aware rate outage experienced by a typical connected and autonomous vehicle (CAV) in a given THz vehicular network. The derived model captures the impact of line-of-sight (LOS) Nakagami-m fading channels, interference, and molecular absorption effects. We first derive the statistics of the interference-plus-molecular absorption noise ratio and demonstrate that it can be approximated by Gamma distribution using Welch-Satterthwaite approximation. Then, we show that the distribution of signal-to-interference-plus-molecular absorption noise ratio (SINR) follows a generalized Beta prime distribution. Based on this, a closed-form HO-aware rate outage expression is derived. Finally, we formulate and solve a CAVs' traffic flow maximization problem to optimize the base-stations (BSs) density and speed of CAVs with collision avoidance, rate outage, and CAVs' minimum traffic flow constraint. The CAVs' traffic flow is modeled using Log-Normal distribution. Our numerical results validate the accuracy of the derived expressions using Monte-Carlo simulations and discuss useful insights related to optimal BS density and CAVs' speed as a function of crash intensity level, THz molecular absorption effects, minimum road-traffic flow and rate requirements, and maximum speed and rate outage limits.

Resource Allocation and Performance Analysis of Hybrid RSMA-NOMA in the Downlink

Rate splitting multiple access (RSMA) and non-orthogonal multiple access (NOMA) are the key enabling multiple access techniques to enable massive connectivity. However, it is unclear whether RSMA would consistently outperform NOMA from a system sum-rate perspective, users' fairness, as well as convergence and feasibility of the resource allocation solutions. This paper investigates the weighted sum-rate maximization problem to optimize power and rate allocations in a hybrid RSMA-NOMA network. In the hybrid RSMA-NOMA, by optimally allocating the maximum power budget to each scheme, the BS operates on NOMA and RSMA in two orthogonal channels, allowing users to simultaneously receive signals on both RSMA and NOMA. Based on the successive convex approximation (SCA) approach, we jointly optimize the power allocation of users in NOMA and RSMA, the rate allocation of users in RSMA, and the power budget allocation for NOMA and RSMA considering successive interference cancellation (SIC) constraints. Numerical results demonstrate the trade-offs that hybrid RSMA-NOMA access offers in terms of system sum rate, fairness, convergence, and feasibility of the solutions.