On the Performance of Cell-Free Massive MIMO With Mixed-ADC Under Rician Fading Channels

Zhang, Yao; Zhou, Meng; Cao, Haotong; Yang, Longxiang; Zhu, Hongbo

doi:10.1109/lcomm.2019.2947462

Cited by 68 publications

(37 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Considering spatial correlation and a LOS component in the link between an AP and a MS leads to a spatially correlated Ricean fading channel model. Spatially correlated Rayleigh fading channels were considered for CF massive MIMO in [18]- [21], whilst uncorrelated Ricean fading channels were examined in [17], [22]- [24], among others, though none of them have addressed the channel hardening phenomenon. In [25] a spatially correlated Ricean fading channel model is assumed, though pilot contamination is not considered and the UL segment is not addressed.…”

Section: A Problem Statement and Related Workmentioning

confidence: 99%

“…Achievable DL/UL rates for single-antenna CF massive MIMO were first derived in [5] based on the classical massive MIMO literature leading to closed-form expressions valid for the CB/MF processing. Extending these expressions to the multi-antenna scenario leads to very straightforward computation (see, for instance, [6], [43]), while calculations when assuming spatial correlation or a LOS component can be found in the recent CF literature [17]- [24]. In this section we further develop the DL and UL achievable user rates previously given in the literature for the proposed spatially correlated Ricean fading channel model.…”

Section: Achievable Ratesmentioning

confidence: 99%

See 1 more Smart Citation

Channel Hardening in Cell-Free and User-Centric Massive MIMO Networks With Spatially Correlated Ricean Fading

et al. 2020

View full text Add to dashboard Cite

The irruption of the cell-free (CF) massive multiple-input multiple-output (MIMO) network topology has meant taking one step further the concept of massive MIMO as a means to provide uniform service in large coverage areas. A key property of massive MIMO networks is channel hardening, by which the channel becomes deterministic when the number of antennas grows large enough relative to the number of serviced users, easing the signal processing and boosting the performance of simple precoders. However, in CF massive MIMO, the fulfillment of this condition depends on several aspects that are not considered in classical massive MIMO systems. In this work, we address the presence of channel hardening in both CF massive MIMO and the recently appeared user-centric (UC) approach, under a spatially correlated Ricean fading channel using distributed and cooperative precoding and combining schemes and different power control strategies for both the downlink (DL) and uplink (UL) segments. We show that the lineof-sight (LOS) component, spatially correlated antennas and UC schemes have an impact on how the channel hardens. In addition, we examine the existent gap between the estimated achievable rate and the true network performance when channel hardening is compromised. Exact closed-form expressions for both the hardening metric and achievable DL/UL rates are given as well. INDEX TERMS Cell-Free, Massive MIMO, User-Centric, Correlated Ricean Fading, Channel Hardening.

show abstract

Section: A Problem Statement and Related Workmentioning

confidence: 99%

Section: Achievable Ratesmentioning

confidence: 99%

Channel Hardening in Cell-Free and User-Centric Massive MIMO Networks With Spatially Correlated Ricean Fading

et al. 2020

View full text Add to dashboard Cite

show abstract

“…However, it is noticed that the use of low-resolution ADCs results in performance degradation in the high signal-tonoise ratio (SNR) regime. As a result, a mixture of low and high precision ADCs is conducted in [10]- [12] to approach a more appropriate trade-off between the ASR and EE. To achieve the optimized EE forthright, both the exhaustive algorithm (EA) and the greedy algorithm (GA) are proposed in [13] on a basis of the EE maximization criterion.…”

Section: A Related Work and Motivationsmentioning

confidence: 99%

Dynamic ADC Resolution-Mapping for Millimeter-Wave Massive MIMO Systems

Lin

2021

IEEE Access

View full text Add to dashboard Cite

The radio-frequency (RF) chains, phase shifters (PSs), and analog-to-digital converters (ADCs) play the dominant role of power consumption in the uplink hybrid millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) networks. To mitigate power consumption, an energyefficient switch and inverter (SI) based partially-connected (PC) architecture with the Gram-Schmidt (GS) antenna selection strategy is addressed. The design of a variable-resolution ADC configuration is addressed under an independent upper bound of power consumption for each ADC in this paper. However, the resulting ADC resolution mapping becomes more complicated due to variant ADC power bounds. A simple ADC bit-allocation algorithm, namely, the sum-resolution (SR) ADC, is proposed.By replacing the total power constraint on ADCs to improve both the achievable sum-rate (ASR) and energy efficiency (EE) performance of the hybrid mmWave massive MIMO system. The SR-ADC solutions in closed form reveal that the optimal ADC resolution is proportional to the square power of the signal-to-noise ratio (SNR) in RF chains. Simulation results demonstrate that the proposed SR-ADC approach offers enhanced improvements on the ASR and EE, and exhibits prominent advantages on the number of activated RF chains compared with the fixed total power system.

show abstract

“…Explicitly, cell‐free massive MIMO refers to the system enables a great number of distributed access points (APs) to coherently serve a lower number of users in the same resource blocks. By combining the merits of distributed massive MIMO and network MIMO systems, cell‐free massive MIMO system leads to an ability to dramatically boost the channel capacity and energy efficiency 8,9 …”

Section: Introductionmentioning

confidence: 99%

Sum‐rate maximization in uplink cell‐free massive multiinput multioutput system with jamming

Zhang

Zhou

Cao

et al. 2020

Trans Emerging Tel Tech

Self Cite

View full text Add to dashboard Cite

This article takes the first look at jamming attacks on both uplink training and data transmission phases in uplink cell‐free massive multi‐input multi‐output systems. Closed‐form rate expressions for that system are derived, which provide us with the opportunities to analyze the achievable rate in the presence of jamming. To compensate for the sum‐rate degradation caused by jamming, we propose an iterative sum‐rate maximization power control algorithm without redesigning the estimator and receiver. Specifically, by virtue of the Lagrange multiplier methodology, the proposed algorithm can determine the closed‐form solution to each iteration and thus, benefiting from less runtime. Simulation results reveal the effectiveness of the proposed algorithm.

show abstract

On the Performance of Cell-Free Massive MIMO With Mixed-ADC Under Rician Fading Channels

Cited by 68 publications

References 9 publications

Channel Hardening in Cell-Free and User-Centric Massive MIMO Networks With Spatially Correlated Ricean Fading

Channel Hardening in Cell-Free and User-Centric Massive MIMO Networks With Spatially Correlated Ricean Fading

Dynamic ADC Resolution-Mapping for Millimeter-Wave Massive MIMO Systems

Sum‐rate maximization in uplink cell‐free massive multiinput multioutput system with jamming

Contact Info

Product

Resources

About