Interference Mitigation via Rate-Splitting and Common Message Decoding in Cloud Radio Access Networks

Responding to the unprecedented challenges imposed by the 5G technologies, mobile operators have given significant attention to Heterogeneous Cloud Radio Access Networks (H-CRAN) due to their beneficial features of performing optimization, cost effectiveness, and improving spectral and energy efficiency performance. H-CRAN inherits the attractive benefits of Heterogeneous Networks (HetNet) and the cloud computing by facilitating interference mitigation, scalability, and radio resource control. Consequently, H-CRAN is proposed in this article as a cost-effective potential solution to alleviate intertier interference and improve cooperative processing gains in HetNets by employing cloud computing. H-CRAN can provide efficient resource sharing at the spectrum, network, and infrastructure levels. Therefore, this article proposes H-CRAN cooperative interference mitigation method that enhances the time sharing among Radio Remote Heads (RRH) users. The study proposes an enhanced Almost Blank Subframe (ABSF) technique to increase the SINR and throughput of the small-cell (low power base station) and macrocell users. Simulation results show that the proposed Dynamic Programming-Diverse Almost Blank Subframe (ABSF) Pattern (DP-DAP) scheme improved the macro- and small-cell users up to 56% and 35%, respectively, as compared to other state-of-the-art ABSF schemes.

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Rate-Splitting Multiple Access in Cache-Aided Cloud-Radio Access Networks

Frontiers in Communications and Networks ◽

10.3389/frcmn.2021.716620 ◽

2021 ◽

Vol 2 ◽

Author(s):

Robert-Jeron Reifert ◽

Alaa Alameer Ahmad ◽

Yijie Mao ◽

Aydin Sezgin ◽

Bruno Clerckx

Keyword(s):

Multiple Access ◽

Access Networks ◽

Mixed Integer ◽

Transmission Scheme ◽

Common Part ◽

Multicast Transmission ◽

Cloud Radio Access Networks ◽

Radio Access Networks ◽

Radio Access ◽

Rate Splitting

Rate-splitting multiple access (RSMA) has been recognized as a promising physical layer strategy for 6G. Motivated by the ever-increasing popularity of cache-enabled content delivery in wireless communications, this paper proposes an innovative multigroup multicast transmission scheme based on RSMA for cache-aided cloud-radio access networks (C-RAN). Our proposed scheme not only exploits the properties of content-centric communications and local caching at the base stations (BSs) but also incorporates RSMA to better manage interference in multigroup multicast transmission with statistical channel state information (CSI) known at the central processor (CP) and the BSs. At the RSMA-enabled cloud CP, the message of each multicast group is split into a private and a common part with the former private part being decoded by all users in the respective group and the latter common part being decoded by multiple users from other multicast groups. Common message decoding is done for the purpose of mitigating the interference. In this work, we jointly optimize the clustering of BSs and the precoding with the aim of maximizing the minimum rate among all multicast groups to guarantee fairness serving all groups. The problem is a mixed-integer nonlinear stochastic program (MINLSP), which is solved by a practical algorithm we propose including a heuristic clustering algorithm for assigning a set of BSs to serve each user followed by an efficient iterative algorithm that combines the sample average approximation (SAA) and weighted minimum mean square error (WMMSE) to solve the stochastic non-convex subproblem of precoder design. Numerical results show the explicit max-min rate gain of our proposed transmission scheme compared to the state-of-the-art trivial interference processing methods. Therefore, we conclude that RSMA is a promising technique for cache-aided C-RAN.

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