Signal-to-Interference-Noise Ratio (SINR) and Signal-to-Noise Ratio (SNR) Improvement in the Massive Multiple-Input Multiple-Output (MIMO) Systems

2020 ◽  
Author(s):  
Garima Kulshreshtha ◽  
Usha Chauhan
Keyword(s):  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Signal To Noise ◽  
Interference Noise ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Snr Improvement ◽  
Noise Ratio

scholarly journals Adaptive Threshold-Aided K-Best Sphere Decoding for Large MIMO Systems

2019 ◽  
Vol 9 (21) ◽  
pp. 4624
Author(s):  
Uzokboy Ummatov ◽  
Kyungchun Lee
Keyword(s):  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Threshold Value ◽  
Adaptive Threshold ◽  
Sphere Decoding ◽  
High Signal ◽  
Signal To Noise ◽  
Multiple Input ◽  
Input Multiple Output

This paper proposes an adaptive threshold-aided K-best sphere decoding (AKSD) algorithm for large multiple-input multiple-output systems. In the proposed scheme, to reduce the average number of visited nodes compared to the conventional K-best sphere decoding (KSD), the threshold for retaining the nodes is adaptively determined at each layer of the tree. Specifically, we calculate the adaptive threshold based on the signal-to-noise ratio and index of the layer. The ratio between the first and second smallest accumulated path metrics at each layer is also exploited to determine the threshold value. In each layer, in addition to the K paths associated with the smallest path metrics, we also retain the paths whose path metrics are within the threshold from the Kth smallest path metric. The simulation results show that the proposed AKSD provides nearly the same bit error rate performance as the conventional KSD scheme while achieving a significant reduction in the average number of visited nodes, especially at high signal-to-noise ratios.

MIMO Detectors: A Comprehensive Performance Analysis

2021 ◽  
Vol 16 (3) ◽  
pp. 24-27
Author(s):  
E. Obi ◽  
B.O. Sadiq ◽  
O.S . Zakariyya ◽  
A. Theresa
Keyword(s):  
Error Rate ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Symbol Error Rate ◽  
Signal To Noise ◽  
High Data ◽  
Noise Ratio ◽  
Better Than

Multiple-input multiple-output (MIMO) systems are increasingly becoming popular due to their ability to multiply data rates without any expansion in the bandwidth. This is critical in this era of high-data rate applications but limited bandwidth. MIMO detectors play an important role in ensuring effective communication in such systems and as such the performance of the following are compared in this paper with respect to symbol error rate (SER) versus signal-to-noise ratio (SNR): maximum likelihood (ML), zero forcing (ZF), minimum mean square error (MMSE) and vertical Bell laboratories layered space time (VBLAST). Results showed that the ML has the best performance as it has the least Symbol Error Rate (SER) for all values of Signal to Noise Ratio (SNR) as it was 91.9% better than MMSE, 99.6% better than VBLAST and 99.8% better than ZF at 20db for a 2x2 antenna configuration., it can also be deduced that the performance increased with increase in number of antenna for all detectors except the V-BLAST detector.

scholarly journals Gyre Precoding and T-Transformation-Based GFDM System for UAV-Aided mMTC Network

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2915
Author(s):  
Joarder Jafor Sadique ◽  
Shaikh Enayet Ullah ◽  
Raad Raad ◽  
Md. Rabiul Islam ◽  
Md. Mahbubar Rahman ◽  
...  
Keyword(s):  
Channel Coding ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Mobility Model ◽  
Base Station ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Aerial Vehicle ◽  
Noise Ratio ◽  
User Interference

In this paper, an unmanned aerial vehicle (UAV)-aided multi-antenna configured downlink mmWave cooperative generalized frequency division multiplexing (GFDM) system is proposed. To provide physical layer security (PLS), a 3D controlled Lorenz mapping system is introduced. Furthermore, the combination of T-transformation spreading codes, walsh Hadamard transform, and discrete Fourier transform (DFT) techniques are integrated with a novel linear multi-user multiple-input multiple-output (MU-MIMO) gyre precoding (GP) for multi-user interference reduction. Furthermore, concatenated channel-coding with multi-user beamforming weighting-aided maximum-likelihood and zero forcing (ZF) signal detection schemes for an improved bit error rate (BER) are also used. The system is then simulated with a single base station (BS), eight massive machine-type communications (mMTC) users, and two UAV relay stations (RSs). Numerical results reveal the robustness of the proposed system in terms of PLS and an achievable ergodic rate with signal-to-interference-plus-noise ratio (SINR) under the implementation of T-transformation scheme. By incorporating the 3D mobility model, brownian perturbations of the UAVs are also analyzed. An out-of-band (OOB) reduction of 320 dB with an improved BER of 1×10−4 in 16-QAM for a signal-to-noise ratio, Eb/N0, of 20 dB is achieved.

scholarly journals Effects of Path Visibility on Urban MIMO Systems

1970 ◽  
Vol 5 (1) ◽  
pp. 22-30
Author(s):  
Sirichai Hemrungrote ◽  
Toshikazu Hori ◽  
Mitoshi Fujimoto ◽  
Kentaro Nishimori
Keyword(s):  
Channel Capacity ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Propagation Characteristics ◽  
Simple Method ◽  
Limited Bandwidth ◽  
Multiple Input ◽  
Input Multiple Output

Multiple-Input Multiple-Output (MIMO) wireless communication technology is expected to improve the channel capacity over the limited bandwidth of existing networks. Since urban MIMO systems have complex propagation characteristics, the channel capacity cannot be estimated using a simple method. Hence, we introduce channel capacity characteristics to urban MIMO systems by using a combination of imaging and ray-launching methods as a ray-tracing scheme. A simulation based on these methods with variable parameters can reproducibly estimate various urban propagation characteristics and discriminate the effects of the urban model and antenna configurations. The characteristics of the Signal-to-Noise Ratio (SNR), the channel capacity, the spatial correlation, as well as the path visibility are then determined from the results of the simulation. The parameter called path visibility introduced in our previous study is considered again herein. We clarify that only this single parameter can be used to determine the channel capacity characteristics in urban MIMO scenarios. This parameter also provides guidance in determining the appropriate range for the base station (BS) height.

scholarly journals Save and Transmit Scheme for Energy Harvesting MIMO Systems with TAS/MRC

2019 ◽  
Vol 15 (1) ◽  
pp. 52-58 ◽  
Author(s):  
Issa Chihaoui ◽  
Mohamed Lassaad Ammari
Keyword(s):  
Energy Harvesting ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Random Variable ◽  
Symbol Error Rate ◽  
Cumulative Distribution ◽  
Multiple Input ◽  
Flat Fading ◽  
Input Multiple Output

In this paper, we propose and analyze a wirelesstransmitter, for multiple-input multiple-output (MIMO) systems,that relies exclusively on energy harvesting. We consider wirelesstransceivers where the transmitter harvests the total requiredenergy from its environment through various sources. We assumethat both transmitter and receiver are equipped with multipleantennas. At the transmitter, a single transmit antenna thatmaximizes the signal-to-noise ratio (SNR) at the receiver isselected for transmission. The remaining antennas are used forenergy harvesting. At the receiver side, maximal-ratio com-bining (MRC) is used. Furthermore, we assume that all theharvested power is used to power the transmitter immediately.The performance of the proposed scheme is analyzed in terms ofoutage probability (OP), symbol error rate (SER) and channelcapacity. The harvested energy comes from random sourcesand is considered as a random variable. Assuming that theharvested power follows a gamma distribution and the MIMOchannel is a Rayleigh flat fading process, we derive a closed-form expressions for the exact cumulative distribution function(CDF) and probability density function (PDF) of the SNR. Basedon this, we analyze the performance of the proposed energyharvesting scheme. The obtained analytical results are validatedby comparing them with the results of Monte-Carlo simulations.

PROBLEM STATEMENT OF JOINT ANTENNA SELECTION AND PRECODING IN MASSIVE MIMO COMMUNICATION SYSTEMS

2021 ◽  
Author(s):  
В.Б. КРЕЙНДЕЛИН ◽  
М.В. ГОЛУБЕВ
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Research Areas ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Legal Restrictions ◽  
Multiple Transmission

Совместный с прекодингом автовыбор антенн на приемной и передающей стороне - одно из перспективных направлений исследований для реализации технологий Multiple Transmission and Reception Points (Multi-TRP, множество точек передачи и приема) в системах со многими передающими и приемными антеннами Massive MIMO (Multiple-Input-Multiple-Output), которые активно развиваются в стандарте 5G. Проанализированы законодательные ограничения, влияющие на применимость технологий Massive MIMO, и специфика реализации разрабатываемого алгоритма в миллиметровомдиапа -зоне длин волн. Рассмотрены алгоритмы формирования матриц автовыбора антенн как на передающей, так и на приемной стороне. Сформулирована строгая математическая постановка задачи для двух критериев работы алгоритма: максимизация взаимной информации и минимизация среднеквадратичной ошибки. Joint precoding and antenna selection both on transmitter and receiver sides is one of the promising research areas for evolving toward the Multiple Transmission and Reception Points (Multi-TRP) concept in Massive MIMO systems. This technology is under active development in the coming 5G 3GPP releases. We analyze legal restrictions for the implementation of 5G Massive MIMO technologies in Russia and the specifics of the implementation of the developed algorithm in the millimeter wavelength range. Algorithms of antenna auto-selection matrices formation on both transmitting and receiving sides are considered. Two criteria are used for joint antenna selection and precoding: maximizing mutual information and minimizing mean square error.

scholarly journals MIMO Self-Encoded Spread Spectrum with Iterative Detection over Rayleigh Fading Channels

2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
Shichuan Ma ◽  
Lim Nguyen ◽  
Won Mee Jang ◽  
Yaoqing (Lamar) Yang
Keyword(s):  
Fading Channels ◽  
Spread Spectrum ◽  
Rayleigh Fading ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Spatial Diversity ◽  
Iterative Detection ◽  
Channel Fading ◽  
Input Multiple Output

Self-encoded spread spectrum (SESS) is a novel communication technique that derives its spreading code from the randomness of the source stream rather than using conventional pseudorandom noise (PN) code. In this paper, we propose to incorporate SESS in multiple-input multiple-output (MIMO) systems as a means to combat against fading effects in wireless channels. Orthogonal space-time block-coded MIMO technique is employed to achieve spatial diversity, and the inherent temporal diversity in SESS modulation is exploited with iterative detection. Simulation results demonstrate that MIMO-SESS can effectively mitigate the channel fading effect such that the system can achieve a bit error rate of with very low signal-to-noise ratio, from 3.3 dB for a antenna configuration to just less than 0 dB for a configuration under Rayleigh fading. The performance improvement for the case is as much as 6.7 dB when compared to an MIMO PN-coded spread spectrum system.

scholarly journals Beam division multiple access for millimeter wave massive MIMO: Hybrid zero-forcing beamforming with user selection

2022 ◽  
Vol 12 (1) ◽  
pp. 445
Author(s):  
Hong Son Vu ◽  
Kien Truong ◽  
Minh Thuy Le
Keyword(s):  
Multiple Access ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Zero Forcing ◽  
Multiuser Interference ◽  
Novel Approach ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Promising Solution

<p>Massive multiple-input multiple-output (MIMO) systems are considered a promising solution to minimize multiuser interference (MUI) based on simple precoding techniques with a massive antenna array at a base station (BS). This paper presents a novel approach of beam division multiple access (BDMA) which BS transmit signals to multiusers at the same time via different beams based on hybrid beamforming and user-beam schedule. With the selection of users whose steering vectors are orthogonal to each other, interference between users is significantly improved. While, the efficiency spectrum of proposed scheme reaches to the performance of fully digital solutions, the multiuser interference is considerably reduced.</p>

scholarly journals Performance Analysis of Rate Splitting in Massive MIMO Systems with Low Resolution ADCs/DACs

2021 ◽  
Vol 11 (20) ◽  
pp. 9409
Author(s):  
Roger Kwao Ahiadormey ◽  
Kwonhue Choi
Keyword(s):  
Mimo Systems ◽  
Mimo System ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Quantization Noise ◽  
High Signal ◽  
Low Resolution ◽  
Rate Splitting ◽  
Noise Ratio

In this paper, we propose rate-splitting (RS) multiple access to mitigate the effects of quantization noise (QN) inherent in low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs). We consider the downlink (DL) of a multiuser massive multiple-input multiple-output (MIMO) system where the base station (BS) is equipped with low-resolution ADCs/DACs. The BS employs the RS scheme for data transmission. Under imperfect channel state information (CSI), we characterize the spectral efficiency (SE) and energy efficiency (EE) by deriving the asymptotic signal-to-interference-and-noise ratio (SINR). For 1-bit resolution, the QN is very high, and the RS scheme shows no rate gain over the non-RS scheme. As the ADC/DAC resolution increases (i.e., 2–3 bits), the RS scheme achieves higher SE in the high signal-to-noise ratio (SNR) regime compared to that of the non-RS scheme. For a 3-bit resolution, the number of antennas can be reduced by 27% in the RS scheme to achieve the same SE as the non-RS scheme. Low-resolution DACs degrades the system performance more than low-resolution ADCs. Hence, it is preferable to equip the system with low-resolution ADCs than low-resolution DACs. The system achieves the best SE/EE tradeoff for 4-bit resolution ADCs/DACs.

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