User Subgrouping in Scalable Cell-Free Massive MIMO Multicasting Systems

Cell-free massive multiple-input multiple-output (CF-mMIMO) is a breakthrough technology for beyond-5G systems, designed to significantly boost the energy and spectral efficiencies of future mobile networks while ensuring a consistent quality of service for all users. Additionally, multicasting has gained considerable attention recently because physical-layer multicasting offers an efficient method for simultaneously serving multiple users with identical service demands by sharing radio resources. Typically, multicast services are delivered either via unicast transmissions or a single multicast transmission. This work, however, introduces a novel subgroup-centric multicast CF-mMIMO framework that divides users into several multicast subgroups based on the similarities in their spatial channel characteristics. This approach allows for efficient sharing of the pilot sequences used for channel estimation and the precoding filters used for data transmission. The proposed framework employs two scalable precoding strategies: centralized improved partial MMSE (IP-MMSE) and distributed conjugate beam-forming (CB). Numerical results show that for scenarios where users are uniformly distributed across the service area, unicast transmissions using centralized IP-MMSE precoding are optimal. However, in cases where users are spatially clustered, multicast subgrouping significantly improves the sum spectral efficiency (SE) of the multicast service compared to both unicast and single multicast transmission. Notably, in clustered scenarios, distributed CB precoding outperforms IP-MMSE in terms of per-user SE, making it the best solution for delivering multicast content.

Performance Analysis and Optimisation of FFR-Aided OFDMA Networks using Channel-Aware Scheduling

Modern cellular standards typically incorporate interference coordination schemes allowing near universal frequency reuse while preserving reasonably high spectral efficiencies over the whole coverage area. In particular, fractional frequency reuse (FFR) and its variants are deemed to play a fundamental role in the next generation of cellular deployments (B4G/5G systems). This paper presents an analytical framework allowing the downlink performance evaluation of FFR-aided OFDMA networks when using channel-aware scheduling policies. Remarkably, the framework contemplates the use of different rate allocation strategies, thus allowing to assess the network behaviour under ideal (capacity-based) or realistic (throughput-based) conditions. Analytical performance results are used to optimise the FFR parameters as a function of, for instance, the resource block scheduling policy or the density of UEs per cell. Furthermore, different optimisation designs of the FFR component are proposed that allow a tradeoff between throughput performance and fairness by suitably dimensioning the FFR-defined cell-centre and cell-edge areas and the corresponding frequency allocation to each region. Numerical results serve to confirm the accuracy of the proposed analytical model while providing insight on how the different parameters and designs affect network performance.

Statistical Analysis and Optimization of a Fifth-Percentile User Rate Constrained Design for FFR/SFR-Aided OFDMA-Based Cellular Networks

Interference mitigation strategies are deemed to play a key role in the context of the next generation (B4G/5G) of multicellular networks based on orthogonal frequency division multiple access. Fractional and soft frequency reuse (FFR, SFR) constitute two powerful mechanisms for intercell interference coordination that have been already adopted by emerging cellular deployments as an efficient way to improve the throughput performance perceived by cell-edge users. This paper presents a novel optimal fifth-percentile user rate constrained design for FFR/SFR-based networks that, by appropriately dimensioning the center and edge regions of the cell, rightly splitting the available bandwidth among these two areas while assigning the corresponding transmit power, allows a tradeoff between cell throughput performance and fairness to be established. To this end, both the cumulative distribution function of the user throughput and the average spectral efficiency of the system are derived assuming the use of the ubiquitous proportional fair scheduling policy. The mathematical framework is then used to obtain numerical results showing that the novel proposed design clearly outperforms previous schemes in terms of throughput fairness control due to a more rational compromise between average cell throughput and cell-edge ICIC.