Abstract
We consider the problem of uplink signal detection in scalable cell-free mMIMO (CF-mMIMO) systems subject to limited fronthaul link capacity and highly correlated channel conditions. Unlike centralized MIMO systems, in which all receive antennas are placed at a central access point (CAP), in the CF-mMIMO architecture the CAP serving a given area also uses information ( i.e. channel estimates and receive signals) collected by a set of surrounding access points (APs). For such a scenario, two new robust receivers are designed, which can combat the effects of limited fronthaul capacity by leveraging knowledge of the heteroscedastic covariance of the resulting effective noise. The first receiver, which has a higher complexity but yields the best performance, is based on an expectation propagation (EP) approach, while the second employs the effective noise heteroscedastic covariance in a generalized least squares (GLS) variation of the maximum likelihood (ML) detection problem. Simulation results confirm the efficacy of both proposed receivers, which are further employed to empirically study the optimum distribution of antennas among the CAP and APs.
Highlights
With the ever-growing demand for higher data rates, lower latency and greater coverage, multiple-input multiple-output (MIMO) systems will continue to develop as a key technology to meet the heterogeneous requirements of the fifth generation (5G) and sixth generation (6G) networks [1], incorporating higher frequency bands and a larger number of antennas
Insights on Optimal Antenna Concentration Ratio: Making use of the proposed robust receivers, a simulation-based study of the performances achieved under different CF-massive MIMO (mMIMO) configurations is performed, which shows that depending on the capacity limitations of fronthaul links, different ratios between the number of antennas concentrated at the central access point (CAP) versus those distributed to access points (APs) should be selected in order to optimize the system performance
We presented two new robust receivers for CF-mMIMO which exploit knowledge of the covariance of the compression noise resulting from passing information through fronthaul links with limited capacities, in order to mitigate the effect of the associated noise heteroscedasticity
Summary
With the ever-growing demand for higher data rates, lower latency and greater coverage, multiple-input multiple-output (MIMO) systems will continue to develop as a key technology to meet the heterogeneous requirements of the fifth generation (5G) and sixth generation (6G) networks [1], incorporating higher frequency bands and a larger number of antennas. K.Ando et al.: Uplink Signal Detection for Scalable Cell-Free Massive MIMO Systems with Robustness to Rate-Limited Fronthaul addressed by the dynamic cooperation clustering (DCC) method [8], in which the CPU-AP connections change dynamically so as to form local clusters [7]–[10], composed of local CPUs assisted by a number of distributed APs that gather observations for actual multiuser symbol detection This architecture is proposed in various related articles [11]–[17] and aims to add feasibility to CF-mMIMO systems, since connecting a massive number of APs directly to a single CPU via perfect fronthaul links is unfeasible due to the associated equipment and maintenance costs. Insights on Optimal Antenna Concentration Ratio: Making use of the proposed robust receivers, a simulation-based study of the performances achieved under different CF-mMIMO configurations is performed, which shows that depending on the capacity limitations of fronthaul links, different ratios between the number of antennas concentrated at the CAP versus those distributed to APs should be selected in order to optimize the system performance
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