Temat: massive MIMO - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Improved Water-Filling Power Allocation for Energy-Efficient Massive MIMO Downlink Transmissions
Autorzy:: Noor Shahida, M. K.
Nordin, R.
Insmail, M.
Tematy:: energy efficiency
Massive MIMO
power allocation
spectral efficiency; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/227000.pdf Link otwiera się w nowym oknie
Opis:: Energy Efficiency (EE) is becoming increasingly important for wireless communications and has caught more attention due to steadily rising energy costs and environmental concerns. Recently, a new network architecture known as Massive Multiple-Input Multiple-Output (MIMO) has been proposed with the remarkable potential to achieve huge gains in EE with simple linear processing. In this paper, a power allocation algorithm is proposed for EE to achieve the optimal EE in Massive MIMO. Based on the simplified expression, we develop a new algorithm to compute the optimal power allocation algorithm and it has been compared with the existing scheme from the previous literature. An improved water filling algorithm is proposed and embedded in the power allocation algorithm to maximize EE and Spectral Efficiency (SE). The numerical analysis of the simulation results indicates an improvement of 40% in EE and 50% in SE at the downlink transmission, compared to the other existing schemes. Furthermore, the results revealed that SE does not influence the EE enhancement after using the proposed algorithm as the number of Massive MIMO antenna at the Base Station (BS) increases.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Propagation and Network Analysis for a Dipole Based Massive Mimo Antenna for 5G Base Stations
Autorzy:: Pushpa, Anita Jones Mary
Chrysolite, Samuelraj
Tematy:: 5G antenna
massive MIMO
dipole array
maximum gain; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/2124749.pdf Link otwiera się w nowym oknie
Opis:: In today’s fast-paced world, where everyone/everything is moving towards an online platform, the need to provide high-speed data to all is inevitable. Hence, introducing the emerging 5G technology with orthogonal frequency division multiplexing integrated with massive MIMO technology is the need of the hour. A 640 port Massive MIMO (m-MIMO) antenna with high evenly spread gain and very low delay, along with a practically possible data rate operating in the mm waveband, is proposed for a 5G base station. The individual antenna element consists of a dipole (λ=0.5cm) designed to operate at 57GHz. Placing the cylindrical MIMO antenna array (8x20) facing the four directions forming the m-MIMO antenna (160x4) at the height of 3m from ground level for simulation. Achievement of a maximum gain of 23.14dBi (θ=90▫) and a minimum data rate of 1.44Gbps with -10dB bandwidth of 2.1GHz (256-QAM) approximately a distance of 478m from the 5G Base station. The m-MIMO structure gives an Envelope Correlation Coefficient of 0.015. The propagation analysis is carried out to substantiate the performance of the proposed system based on field strength and received power. Network Analysis for better reception performance is carried out by changing the antenna height placement, altering the down tilt of the antenna array, and sweeping the polarization angle of the antenna array.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Design of Hybrid Precoder for mm-Wave MIMO System Based on Generalized Triangular Decomposition Method
Autorzy:: Thurpati, Sammaiah
Muthuchidambaranathan, P.
Tematy:: millimeter-wave
mmWave
SVD
GTD
hybrid precoding
massive MIMO; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/2124753.pdf Link otwiera się w nowym oknie
Opis:: Hybrid precoding techniques are lately involved a lot of interest for millimeter-wave (mmWave) massive MIMO systems is due to the cost and power consumption advantages they provide. However, existing hybrid precoding based on the singular value decomposition (SVD) necessitates a difficult bit allocation to fit the varying signal-to-noise ratios (SNRs) of altered sub-channels. In this paper, we propose a generalized triangular decomposition (GTD)-based hybrid precoding to avoid the complicated bit allocation. The development of analog and digital precoders is the reason for the high level of design complexity in analog precoder architecture, which is based on the OMP algorithm, is very non-convex, and so has a high level of complexity. As a result, we suggest using the GTD method to construct hybrid precoding for mmWave mMIMO systems. Simulated studies as various system configurations are used to examine the proposed design. In addition, the archived findings are compared to a hybrid precoding approach in the classic OMP algorithm. The proposed Matrix Decomposition’s simulation results of signal-to-noise ratio vs spectral efficiencies.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Deep Learning-Powered Beamforming for 5G Massive MIMO Systems
Autorzy:: Bendjillali, Ridha Ilyas
Bendelhoum, Mohammed Sofiane
Tadjeddine, Ali Abderrazak
Kamline, Miloud
Tematy:: 5G
digital beamforming
hybrid beamforming
massive MIMO
ResNeSt; Pokaż więcej
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:: https://bibliotekanauki.pl/articles/27312956.pdf Link otwiera się w nowym oknie
Opis:: In this study, a ResNeSt-based deep learning approach to beamforming for 5G massive multiple-input multipleoutput (MIMO) systems is presented. The ResNeSt-based deep learning method is harnessed to simplify and optimize the beamforming process, consequently improving performance and efficiency of 5G and beyond communication networks. A study of beamforming capabilities has revealed potential to maximize channel capacity while minimizing interference, thus eliminating inherent limitations of the traditional methods. The proposed model shows superior adaptability to dynamic channel conditions and outperforms traditional techniques across various interference scenarios.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Throughput, Spectral, and Energy Efficiency of 5G Massive MIMO Applications Using Different Linear Precoding Schemes
Autorzy:: Salah, Ibrahim
Rahouma, Kamel Hussein
Hussein, Aziza I.
Mabrook, M. Mourad
Tematy:: throughput
massive MIMO
spectral efficiency
energy efficiency
trade-off; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/2203002.pdf Link otwiera się w nowym oknie
Opis:: On fifth-generation wireless networks, a potential massive MIMO system is used to meet the ever-increasing request for high-traffic data rates, high-resolution streaming media, and cognitive communication. In order to boost the trade-off between energy efficiency (EE), spectral efficiency (SE), and throughput in wireless 5G networks, massive MIMO systems are essential. This paper proposes a strategy for EE 5G optimization utilizing massive MIMO technology. The massive MIMO system architecture would enhance the trade-off between throughput and EE at the optimum number of working antennas. Moreover, the EE-SE tradeoff is adjusted for downlink and uplink massive MIMO systems employing linear precoding techniques such as Multiple -Minimum Mean Square Error (M-MMSE), Regularized Zero Forcing (RZF), Zero Forcing (ZF), and Maximum Ratio (MR). Throughput is increased by adding more antennas at the optimum EE, according to the analysis of simulation findings. Next, utilizing M MMSE instead of RZF and ZF, the suggested trading strategy is enhanced and optimized. The results indicate that M-MMSE provides the best tradeoff between EE and throughput at the determined optimal ratio between active antennas and active users equipment’s (UE).
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Efficient Iterative Detection Based on Conjugate Gradient and Successive Over-Relaxation Methods for Uplink Massive MIMO Systems
Autorzy:: Labed, Smail
Aounallah, Naceur
Tematy:: computational complexity
conjugate gradient
massive MIMO
relaxation parameter
signal detection; Pokaż więcej
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:: https://bibliotekanauki.pl/articles/24200730.pdf Link otwiera się w nowym oknie
Opis:: Being a crucial aspect of ﬁfth-generation (5G) mobile communications systems, massively multiple-input multipleoutput (mMIMO) architectures are expected to help achieve the highest key performance indicators. However, the huge numbers of antennas used in such systems make it diﬃcult to determine the inversion of the signal channel matrix relied upon by several detection methods, hence posing a problem with accurate estimation of the symbols sent. In this paper, conjugate gradient (CG) and successive over-relaxation (SOR) methods are selected to construct a new iterative approach that avoids the matrix inversion computation issue. This suggested approach for uplink mMIMO detection is based on a joint cascade structure of both iterative methods. The CG method is ﬁrst applied and adjusted for the initial solution, followed by the SOR method in the ﬁnal iterations for terminal computations, resulting in an algorithm with robust performance and low computational complexity. Furthermore, the new hybrid scheme operates based on the relaxation parameter, whose value has a great impact on error performance and, whose optimal determination is necessary. Numerical simulations reveal that the proposed scheme is capable of signiﬁcantly improving signal detection accuracy with minimum complexity. The simulation results indicated that the proposed detector outperforms CG and SOR detectors, achieves close to optimal performance, requires fewer iterations, and reduces complexity.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Comparative Analysis of Procedures and Solutions to Improve Energy Efficiency of Massive MIMO
Autorzy:: Phogat, Ritu Singh
Joshi, Rutvij
Tematy:: EE
Uplink-Downlink Transmission
power control
linear precoding
CF Massive MIMO; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/2200684.pdf Link otwiera się w nowym oknie
Opis:: The blustery growth of high data rate applications leads to more energy consumption in wireless networks to satisfy service quality. Therefore, energy-efficient communications have been paid more attention to limited energy resources and environmentally friendly transmission functioning. Countless publications are present in this domain which focuses on intensifying network energy efficiency for uplink-downlink transmission. It is done either by using linear precoding schemes, by amending the number of antennas per BS, by power control problem formulation, antenna selection schemes, level of hardware impairments, and by considering cell-free (CF) Massive-MIMO. After reviewing these techniques, still there are many barriers to implement them practically. The strategies mentioned in this review show the performance of EE under the schemes as raised above. The chief contribution of this work is the comparative study of how Massive MIMO EE performs under the background of different methods and architectures and the solutions to few problem formulations that affect the EE of network systems. This study will help choose the best criteria to improve EE of Massive MIMO while formulating a newer edition of testing standards. This survey provides the base for interested readers in energy efficient Massive MIMO.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: Power Scaling and Antenna Selection Techniques for Hybrid Beamforming in mmWave Massive MIMO Systems
Autorzy:: Nalband, Abdul Haq
Sarvagya, Mrinal
Ahmed, Mohammed Riyaz
Tematy:: antenna selection
massive MIMO
millimeter Wave
5G
hybrid beamforming
power scaling; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/226190.pdf Link otwiera się w nowym oknie
Opis:: With the advent of massive MIMO and mmWave, Antenna selection is the new frontier in hybrid beamforming employed in 5G base stations. Tele-operators are reworking on the components while upgrading to 5G where the antenna is a last-mile device. The burden on the physical layer not only demands smart and adaptive antennas but also an intelligent antenna selection mechanism to reduce power consumption and improve system capacity while degrading the hardware cost and complexity. This work focuses on reducing the power consumption and finding the optimal number of RF chains for a given millimeter wave massive MIMO system. At first, we investigate the power scaling method for both perfect Channel State Information (CSI) and imperfect CSI where the power is reduced by1/Nᵣ and 1/√Nᵣ respectively. We further propose to reduce the power consumption by emphasizing on the subdued resolution of Analog-to-Digital Converters (ADCs) with quantization awareness. The proposed algorithm selects the optimal number of antenna elements based on the resolution of ADCs without compromising on the quality of reception. The performance of the proposed algorithm shows significant improvement when compared with conventional and random antenna selection methods.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Time-shifted Pilot-based Scheduling with Adaptive Optimization for Pilot Contamination Reduction in Massive MIMO
Autorzy:: Kumar, Ambala Pradeep
Srinivasulu, Tadisetty
Tematy:: massive MIMO
pilot contamination
sparse FCM
time-shifted pilot scheduling
user grouping; Pokaż więcej
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:: https://bibliotekanauki.pl/articles/1839309.pdf Link otwiera się w nowym oknie
Opis:: Massive multiple-input multiple-output (MIMO) is considered to be an emerging technique in wireless communication systems, as it offers the ability to boost channel capacity and spectral efficiency. However, a massive MIMO system requires huge base station (BS) antennas to handle users and suffers from inter-cell interference that leads to pilot contamination. To cope with this, time-shifted pilots are devised for avoiding interference between cells, by rearranging the order of transmitting pilots in different cells. In this paper, an adaptive-elephant-based spider monkey optimization (adaptive ESMO) mechanism is employed for time-shifted optimal pilot scheduling in a massive MIMO system. Here, user grouping is performed with the sparse fuzzy c-means (Sparse FCM) algorithm, grouping users based on such parameters as large-scale fading factor, SINR, and user distance. Here, the user grouping approach prevents inappropriate grouping of users, thus enabling effective grouping, even under the worst conditions in which the channel operates. Finally, optimal time-shifted scheduling of the pilot is performed using the proposed adaptive ESMO concept designed by incorporating adaptive tuning parameters. The efficiency of the adaptive ESMO approach is evaluated and reveals superior performance with the highest achievable uplink rate of 43.084 bps/Hz, the highest SINR of 132.9 dB, and maximum throughput of 2.633 Mbps.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Improved Two-Dimensional Double Successive Projection Algorithm for Massive MIMO Detection
Autorzy:: Chakraborty, Sourav
Sinha, Nirmalendu Bika
Mitra, Monojit
Tematy:: massive MIMO
MMSE
ZF
2D-DSP
QAM
LLR
I2D-DSP; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/2202981.pdf Link otwiera się w nowym oknie
Opis:: In a massive multiple-input multiple-output (MIMO) system, a large number of receiving antennas at the base station can simultaneously serve multiple users. Linear detectors can achieve optimal performance but require large dimensional matrix inversion, which requires a large number of arithmetic operations. Several low complexity solutions are reported in the literature. In this work, we have presented an improved two-dimensional double successive projection (I2D-DSP) algorithm for massive MIMO detection. Simulation results show that the proposed detector performs better than the conventional 2D-DSP algorithm at a lower complexity. The performance under channel correlation also improves with the I2D-DSP scheme. We further developed a soft information generation algorithm to reduce the number of magnitude comparisons. The proposed soft symbol generation method uses real domain operation and can reduce almost 90% flops and magnitude comparisons.
Dostawca treści:: Biblioteka Nauki

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