On the General Analysis of Coordinated Regularized Zero-Forcing Precoding: An Application to Two-Tier Small-Cell Networks

Tataria, Harsh; Smith, Peter J.; Dmochowski, Pawel A.

doi:10.1109/tcomm.2017.2695199

Cited by 21 publications

(47 citation statements)

References 37 publications

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“…The expectation is extremely cumbersome to perform, since it needs to be taken over the myriad of small-scale fading in HH H , a term on the denominator of (6). To overcome this difficulty, we employ the univariate special case of the commonly used firstorder Laplace approximation [9,26,27], allowing us to express (6) as (7) (shown on top of the following page for the reasons of space). The approximation in (7) is a firstorder Laplace expansion and is of the form E{γ/X} ≈ γ/E{X}, where γ is a scalar value.…”

Section: Remarkmentioning

confidence: 99%

“…7]. From single-user MIMO literature, it is known that channel correlation has a negative impact on the terminal and system spectral efficiency (see e.g., [3,[6][7][8][9]27]).…”

Section: Introductionmentioning

confidence: 99%

“…The 1×M propagation channel to terminal from the BS array is denoted by h , which is assumed to follow a spatially correlated Rayleigh fading distribution, i.e., h ∼ CN (0, R ). Unlike previously (see e.g., [8,9]), R , the M × M correlation matrix, is specific to terminal . Naturally, R will be a function of the channel's spatial parameters [6,11,12,14].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Channel Correlation Diversity in MU-MIMO Systems – Analysis and Measurements

Tataria

Sangodoyin

Molisch

et al. 2019

2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

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In multiuser multiple-input multiple-output (MU-MIMO) systems, channel correlation is detrimental to system performance. We demonstrate that widely used, yet overly simplified, correlation models that generate identical correlation profiles for each terminal tend to severely underestimate the system performance. In sharp contrast, more physically motivated models that capture variations in the power angular spectra across multiple terminals, generate diverse correlation patterns. This has a significant impact on the system performance. Assuming correlated Rayleigh fading and downlink zero-forcing precoding, tight closed-form approximations for the average signalto-noise-ratio, and ergodic sum spectral efficiency are derived. Our expressions provide clear insights into the impact of diverse correlation patterns on the above performance metrics. Unlike previous works, the correlation models are parameterized with measured data from a recent 2.53 GHz urban macrocellular campaign in Cologne, Germany. Overall, results from this paper can be treated as a timely re-calibration of performance expectations from practical MU-MIMO systems.

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Section: Remarkmentioning

confidence: 99%

“…7]. From single-user MIMO literature, it is known that channel correlation has a negative impact on the terminal and system spectral efficiency (see e.g., [3,[6][7][8][9]27]).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Channel Correlation Diversity in MU-MIMO Systems – Analysis and Measurements

Tataria

Sangodoyin

Molisch

et al. 2019

2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

Self Cite

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show abstract

“…According to the cognitive radio based paradigm [5], the cognitive network should first protect the primary user from the cognitive interference caused by spectrum sharing, rather than selfishly design its precoding scheme. In this subsection, we consider the proposal of a linear precoder design for the femtocell to nullify the cognitive interference of (7) in a totally autonomous way.…”

Section: Cognitive Interference Alignment Schemes Designmentioning

confidence: 99%

“…More specifically, a tier of IoT oriented femtocell base stations coexists with a tier of pre-existing macrocell base stations (MBSs) and shares the licensed spectrum. This two-tiered deployment aims at breaking away from the traditional cellular layout to provide very high data rates for short-range IoT devices, and reduces the load on the macrocell network [5]. …”

Section: Introductionmentioning

confidence: 99%

Cognitive Interference Alignment Schemes for IoT Oriented Heterogeneous Two-Tier Networks

Tian

Wang

et al. 2018

Sensors

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This paper considers interference management and capacity improvement for Internet of Things (IoT) oriented two-tier networks by exploiting cognition between network tiers with interference alignment (IA). More specifically, we target our efforts on the next generation two-tier networks, where a tier of femtocell serving multiple IoT devices shares the licensed spectrum with a tier of pre-existing macrocell via a cognitive radio. Aiming to manage the cross-tier interference caused by cognitive spectrum sharing as well as ensure an optimal capacity of the femtocell, two novel self-organizing cognitive IA schemes are proposed. First, we propose an interference nulling based cognitive IA scheme. In such a scheme, both co-tier and cross-tier interferences are aligned into the orthogonal subspace at each IoT receiver, which means all the interference can be perfectly eliminated without causing any performance degradation on the macrocell. However, it is known that the interference nulling based IA algorithm achieves its optimum only in high signal to noise ratio (SNR) scenarios, where the noise power is negligible. Consequently, when the imposed interference-free constraint on the femtocell can be relaxed, we also present a partial cognitive IA scheme that further enhances the network performance under a low and intermediate SNR. Additionally, the feasibility conditions and capacity analyses of the proposed schemes are provided. Both theoretical and numerical results demonstrate that the proposed cognitive IA schemes outperform the traditional orthogonal precoding methods in terms of network capacity, while preserving for macrocell users the desired quality of service.

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Spatial Correlation Variability in Multiuser Systems

Tataria¹,

Smith

Molisch

et al. 2018

2018 IEEE International Conference on Communications (ICC)

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Spatial correlation across an antenna array is known to be detrimental to the terminal signal-to-interference-plusnoise-ratio (SINR) and system spectral efficiency. For a downlink multiuser multiple-input multiple-output system (MU-MIMO), we show that the widely used, yet overly simplified, correlation models which generate fixed correlation patterns for all terminals tend to underestimate the system performance. This is in contrast to more sophisticated, yet physically motivated, remote scattering models that generate variations in the correlation structure across multiple terminals. The remote scattering models are parameterized with measured data from a recent 2.53 GHz urban macrocellular channel measurement campaign in Cologne, Germany. Assuming spatially correlated Ricean fading, with maximum-ratio transmission precoding, tight closed-form approximations to the expected (average) SINR, and ergodic sum spectral efficiency are derived. The expressions provide clear insights into the impact of variable correlation patterns on the above performance metrics. Our results demonstrate the sensitivity of the MU-MIMO performance to different correlation models, and provide a cautionary tale of its impact.

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On the General Analysis of Coordinated Regularized Zero-Forcing Precoding: An Application to Two-Tier Small-Cell Networks

Cited by 21 publications

References 37 publications

Channel Correlation Diversity in MU-MIMO Systems – Analysis and Measurements

Channel Correlation Diversity in MU-MIMO Systems – Analysis and Measurements

Cognitive Interference Alignment Schemes for IoT Oriented Heterogeneous Two-Tier Networks

Spatial Correlation Variability in Multiuser Systems

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