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See detailFading-ratio-based selection for massive MIMO systems under line-of-sight propagation
Chaves, Rafael da Silva; Cetin, Ediz; Lima, Markus V. S. et al

in Wireless Networks (2022)

Massive multiple-input multiple-output (MIMO) enables increased throughput by using spatial multiplexing. However, the throughput may severely degrade when the number of users served by a single base ... [more ▼]

Massive multiple-input multiple-output (MIMO) enables increased throughput by using spatial multiplexing. However, the throughput may severely degrade when the number of users served by a single base station increases, especially under line-of-sight (LoS) propagation. Selecting users is a possible solution to deal with this problem. In the literature, the user selection algorithms can be divided into two classes: small-scale fading aware (SSFA) and large scale fading aware (LSFA) algorithms. The LSFA algorithms are good solutions for massive MIMO systems under non LoS propagation since the small-scale fading does not affect the system performance under this type of propagation. For the LoS case, the small scale fading has a great impact on the system performance, requiring the use of SSFA algorithms. However, disregarding the large-scale fading is equivalent to assuming that all users are equidistant from the base station and experience the same level of shadowing, which is not a reasonable approximation in practical applications. To address this shortcoming, a new user selection algorithm called the fading-ratio-based selection (FRBS) is proposed. FRBS considers both fading information to drop those users that induce the highest interference to the remaining ones. Simulation results considering LoS channels show that using FRBS yields near optimum downlink throughput, which is similar to that of the state-of-the-art algorithm, but with much lower computational complexity. Moreover, the use of FRBS with zero forcing precoder resulted in 26.28% improvement in the maximum throughput when compared with SSFA algorithms, and 35.39% improvement when compared with LSFA algorithms. [less ▲]

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See detailUser selection for massive MIMO under line-of-sight propagation
Chaves, Rafael da Silva; Cetin, Ediz; Lima, Markus V. S. et al

in IEEE Open Journal of the Communications Society (2022)

This paper provides a review of user selection algorithms for massive multiple-input multiple-output (MIMO) systems under the line-of-sight (LoS) propagation model. Although the LoS propagation is ... [more ▼]

This paper provides a review of user selection algorithms for massive multiple-input multiple-output (MIMO) systems under the line-of-sight (LoS) propagation model. Although the LoS propagation is extremely important to some promising technologies, like in millimeter-wave communications, massive MIMO systems are rarely studied under this propagation model. This paper fills this gap by providing a comprehensive study encompassing several user selection algorithms, different linear precoders and simulation setups, and also considers the effect of partial channel state information (CSI). One important result is the existence of practical cases in which the LoS propagation model may lead to significant levels of interference among users within a cell; these cases are not satisfactorily addressed by the existing user selection algorithms. Motivated by this issue, a new user selection algorithm based on inter-channel interference (ICI) called ICI-based selection (ICIBS) is proposed. Unlike other techniques, the ICIBS accounts for the ICI in a global manner, thus yielding better results, especially in cases where there are many users interfering with each other. In such scenarios, simulation results show that when compared to the competing algorithms, the proposed approach provided an improvement of at least 10.9% in the maximum throughput and 7.7% in the 95%-probability throughput when half of the users were selected. [less ▲]

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See detailInterference Mitigation via NMF for Radio Astronomy Applications: A Feasibility Study
Silva, Felipe Barboza; Cetin, Ediz; Alves Martins, Wallace UL et al

in 15th International Conference on Sensing Technology (ICST), Sydney 5-7 December 2022 (2022)

This work assesses the feasibility of using nonnegative matrix factorization (NMF) for radio frequency interference (RFI) mitigation in radio astronomy applications. Two NMF-based mitigation approaches ... [more ▼]

This work assesses the feasibility of using nonnegative matrix factorization (NMF) for radio frequency interference (RFI) mitigation in radio astronomy applications. Two NMF-based mitigation approaches are proposed, one using RFI frequency information extracted from the received signals and the other using an RFI template. The suitability and efficacy of these approaches are evaluated by targeting automatic dependent surveillance-broadcast (ADS-B) RFI using data collected from the Parkes radio telescope in Australia. Results show that the proposed approaches can mitigate the RFI with minimal degradation to the underlying observation of a double pulsar, and without discarding any received data, indicating the applicability of NMF-based approaches as potential RFI mitigation tools in radio astronomy applications. [less ▲]

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See detailRadio Frequency Interference Mitigation via Nonnegative Matrix Factorization for GNSS
Silva, Felipe Barboza; Cetin, Ediz; Alves Martins, Wallace UL

in IEEE Transactions on Aerospace and Electronic Systems (2022)

A radio frequency interference (RFI) mitigation approach based on nonnegative matrix factorization (NMF) for global navigation satellite systems (GNSS) signals is proposed. The proposed approach employs ... [more ▼]

A radio frequency interference (RFI) mitigation approach based on nonnegative matrix factorization (NMF) for global navigation satellite systems (GNSS) signals is proposed. The proposed approach employs NMF to separate the interference from the GNSS signals, and it can be deployed in a supervised or semi-blind manner. The supervised NMF framework assumes prior knowledge about the RFI whereas its semi-blind counterpart does not require any a priori information about the RFI. Results indicate that both schemes are able to mitigate narrow and wideband RFI signals, outperforming Kalman, notch filter and wavelet-based techniques, enabling GNSS signal acquisition even in scenarios where the interference is 50 dB stronger than the GNSS signals. In addition, the proposed approach is able to mitigate multiple, different types of RFI corrupting the received GNSS signal. [less ▲]

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See detailRadio Frequency Interference Detection Using Nonnegative Matrix Factorization
Silva, Felipe B.; Cetin, Ediz; Alves Martins, Wallace UL

in IEEE Transactions on Aerospace and Electronic Systems (2021)

This work proposes a new pre-correlation interference detection technique based on nonnegative matrix factorization (NMF) for global navigation satellite system (GNSS) signals. The proposed technique uses ... [more ▼]

This work proposes a new pre-correlation interference detection technique based on nonnegative matrix factorization (NMF) for global navigation satellite system (GNSS) signals. The proposed technique uses NMF to extract the time and frequency properties of the received signal from its spectrogram. The estimated spectral shape is then compared with the spectrogram’s time slices by means of a similarity function to detect the presence of radio frequency interference (RFI). In the presence of RFI, the NMF estimated spectral shape tends to be well-defined, resulting in high similarity levels. In contrast, in the absence of RFI, the received signal is solely comprised of noise and GNSS signals resulting in a noise like spectral shape estimate, leading to considerably reduced similarity levels. The proposal exploits this different similarity levels to detect the presence of interference. Simulation results indicate that the proposed technique yields increased detection capability with low false alarm rate even in low jammer-to-noise ratio environments for both narrow and wideband interference sources without requiring fine-tuning of parameters for specific RFI types. In addition, the proposal has reduced computational complexity, when compared with an existing statistical-based detector. [less ▲]

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See detailUser Selection based on Inter-channel Interference for Massive MIMO under Line-of-sight Propagation
Chaves, Rafael S.; Cetin, Ediz; Lima, Markus V. S. et al

in URSI GASS 2021, Rome 28 August - 4 September 2021 (2021)

Massive multiple-input multiple-output (MIMO) is seen as a key enabler for next-generation wireless communication systems. Increased throughput afforded by massive MIMO, however, may severely degrade when ... [more ▼]

Massive multiple-input multiple-output (MIMO) is seen as a key enabler for next-generation wireless communication systems. Increased throughput afforded by massive MIMO, however, may severely degrade when the number of users served by a single base station increases, calling for user scheduling algorithms. To deal with this problem, a new user selection algorithm, called inter-channel interference-based selection (ICIBS), is proposed. ICIBS drops those users that induce the highest interference to the remaining users. Simulations show that selecting users with ICIBS significantly improves the throughput, outperforming state-of-the-art user selection algorithms. [less ▲]

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See detailDME Interference Mitigation for GNSS Receivers via Nonnegative Matrix Factorization
Silva, Felipe B.; Cetin, Ediz; Alves Martins, Wallace UL

in URSI GASS 2021, Rome 28 August - 4 September 2021 (2021)

In this work a nonnegative matrix factorization based approach is proposed to mitigate the impact of interference due to distance measurement equipment (DME) signals in global navigation satellite system ... [more ▼]

In this work a nonnegative matrix factorization based approach is proposed to mitigate the impact of interference due to distance measurement equipment (DME) signals in global navigation satellite system (GNSS) receivers. The proposed approach operates by separating the DME and GNSS signals, and the results show that it outperforms the traditional pulse-blanking based techniques in terms of acquisition and carrier-to-noise ratio metrics without discarding any of the received signal samples. [less ▲]

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See detailADS-B Signal Detection via Time-Frequency Analysis for Radio Astronomy Applications
Silva, Felipe B.; Cetin, Ediz; Alves Martins, Wallace UL

in IEEE International Symposium on Circuits and Systems (ISCAS), Daegu 22-28 May 2021 (2021)

This paper proposes a time-frequency (TF) domain technique for detecting the presence of automatic dependent surveillance-broadcast (ADS-B) interference signals in radio astronomy applications. The ... [more ▼]

This paper proposes a time-frequency (TF) domain technique for detecting the presence of automatic dependent surveillance-broadcast (ADS-B) interference signals in radio astronomy applications. The proposed technique uses a priori knowledge about the ADS-B signal’s frequency information and compares it with the received signal’s spectrogram time slices via the cosine similarity function. In the presence of ADS-B signals, the similarity levels are higher, whereas in their absence the levels are lower. Hence, the proposed approach exploits this to detect the presence of such signals. Simulation results using signals from the Parkes radio telescope show the efficacy of the proposed method in detecting the presence of ADS-B signals when compared with other classic detectors. [less ▲]

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See detailOn the Convergence of Max-Min Fairness Power Allocation in Massive MIMO Systems
Chaves, Rafael S.; Cetin, Ediz; Lima, Markus V.S. et al

in IEEE Communications Letters (2020)

Power allocation techniques, among which the max-min fairness power allocation (MMFPA) is one of the most widely used, are essential to guarantee good data throughput for all users in a cell. Recently, an ... [more ▼]

Power allocation techniques, among which the max-min fairness power allocation (MMFPA) is one of the most widely used, are essential to guarantee good data throughput for all users in a cell. Recently, an efficient MMFPA algorithm for massive multiple-input multiple-output (MIMO) systems has been proposed. However, this algorithm is susceptible to the initial search interval employed by the underlying bisection search. Even if the optimal point belongs to the initial search interval, this algorithm may fail to converge to such a point. In this paper, we use the Perron-Frobenius theory to explain this issue and provide search intervals that guarantee convergence to the optimal point. Furthermore, we propose the bound test procedure as an efficient way of initializing the search interval. Simulation results corroborate our findings. [less ▲]

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