Precoding Based Downlink OAM-MIMO Communications with Rate Splitting

TL;DR

This work tackles privacy concerns in downlink $OAM$-MIMO by integrating Rate Splitting ($RS$) to divide transmissions into private and common parts and maximize the sum capacity $C_{ ext{sum}}^{ ext{RS}}$. A transmission framework based on concentric Uniform Circular Arrays ($UCAs$) assigns one $OAM$ mode to each user pair while allowing intra-pair RS processing, and a geometry-based channel model yields the channel coefficients $h_{m_k,n_i}$. The core contribution is formulating a nonconvex optimization ${ m P1}$ for the precoding matrix $P$ and solving it via Fractional Programming with quadratic transformation to obtain the optimal $P$; an iterative algorithm updates auxiliary variables until convergence. Simulation results show that the proposed RS-enabled OAM-MIMO system achieves higher sum capacity than traditional schemes, with capacity improving when more independent $OAM$ channels are available and persisting under larger transmit power. The framework demonstrates a practical path toward privacy-aware, high-capacity wireless links using $OAM$ modes and RS.

Abstract

Orbital angular momentum (OAM) and rate splitting (RS) are the potential key techniques for the future wireless communications. As a new orthogonal resource, OAM can achieve the multifold increase of spectrum efficiency to relieve the scarcity of the spectrum resource, but how to enhance the privacy performance imposes crucial challenge for OAM communications. RS technique divides the information into private and common parts, which can guarantee the privacies for all users. In this paper, we integrate the RS technique into downlink OAM-MIMO communications, and study the precoding optimization to maximize the sum capacity. First, the concentric uniform circular arrays (UCAs) are utilized to construct the downlink transmission framework of OAM-MIMO communications with RS. Particularly, users in the same user pair utilize RS technique to obtain the information and different user pairs use different OAM modes. Then, we derive the OAM-MIMO channel model, and formulate the sum capacity maximization problem. Finally, based on the fractional programming, the optimal precoding matrix is obtained to maximize the sum capacity by using quadratic transformation. Extensive simulation results show that by using the proposed precoding optimization algorithm, OAM-MIMO communications with RS can achieve higher sum capacity than the traditional communication schemes.

Figures (6)

• Figure 1: Downlink OAM-MIMO communications with RS
• Figure 2: The performance comparison of OAM communications with different OAM modes
• Figure 3: The capacity performance of OAM communications with multiple OAM modes
• Figure 4: The variation of ${\rm{U}}{{\rm{D}}_{2k-1}}$ capacity with total transmit power
• Figure 5: The ${\rm{U}}{{\rm{D}}_{2k}}$ capacity of different wireless communications versus total transmit power