Research on Multiuser Scheduling Algorithm Based on the Frobenius-Norm of Channel Matrix

2014 ◽  
Vol 687-691 ◽  
pp. 4110-4113
Author(s):  
Yong Bo Zhang ◽  
Jian Xin Li ◽  
Yan Ping Li
Keyword(s):  
Power Distribution ◽  
Mimo System ◽  
Signal To Noise Ratio ◽  
Scheduling Algorithm ◽  
Base Station ◽  
Frobenius Norm ◽  
Channel Matrix ◽  
Water Filling ◽  
Multiuser Scheduling ◽  
Service Application

In MU-MIMO system when a base station sometimes has not enough resources to satisfy the service application from each user, we should arrange to communicate selectively for a certain number of users according to some appropriate method, i.e. multiuser scheduling. Given necessary channel state information this paper investigated the relationship between the norm of channel matrix and channel quality and studied multiuser scheduling algorithm typically based on the Frobenius-norm of channel matrix which was simulated respectively for equal power distribution and water-filling power distribution in MU-MIMO system model. The simulation result showed that at the same transmitted signal-to-noise ratio (SNR) such scheduling algorithm could be able to lower the bit error rate (BER) effectively and improve the receive capability in comparison to random scheduling.

Research on Four Water-Filling Power Distribution Schemes in MU-MIMO System

2014 ◽  
Vol 721 ◽  
pp. 635-638
Author(s):  
Yong Bo Zhang ◽  
Jian Xin Li ◽  
Wei Min Wen
Keyword(s):  
Channel Capacity ◽  
Bit Error Rate ◽  
Error Rate ◽  
Power Distribution ◽  
Mimo System ◽  
Base Station ◽  
Block Diagonalization ◽  
Total Transmission ◽  
Water Filling ◽  
Multiuser Scheduling

It is a key issue to distribute the total transmission power among different data streams leading to larger channel capacity or lower bit error rate at the base station in MU-MIMO system. Based on MU-MIMO system model applying block diagonalization precoding (BDP) this paper presented four kinds of water-filling power distribution schemes which had been simulated for random scheduling and multiuser scheduling. The simulation results showed that respective water-filling power distribution owned maximum channel capacity and united water-filling power distribution resulted in the lowest bit error rate (BER).

Performance Analysis of Low Complexity Multiuser Scheduling Algorithms in MIMO System

2013 ◽  
Vol 392 ◽  
pp. 867-871
Author(s):  
Ming Xia Lv ◽  
Yan Kun Lai ◽  
Dong Tang
Keyword(s):  
Mimo System ◽  
Scheduling Algorithm ◽  
Low Complexity ◽  
Base Station ◽  
User Scheduling ◽  
Sum Capacity ◽  
Multiuser Scheduling ◽  
The Common ◽  
The Cost ◽  
Selection Algorithms

The total throughput of the communication system can be maximized by allocating the common radio resource to the user or the user group having the best channel quality at a given time and the multiuser diversity gain can be obtained when multiple users share the same channel at one time. The object to select the users is to select the users with the maximum sum capacity. As for a scheduling algorithm, exhaustive algorithm can get the largest capability of the system by multi-user scheduling. However, this algorithm is quite complex hence the cost of operation to a base station has substantial increased. We compare the multiuser performance of two fast user selection algorithms with low complexity in MIMO-MRC systems with co-channel interferences. From the simulation results, these two algorithms not only decrease the computational complexity of the scheduling algorithm but also retain large capability of the MIMO system.

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.

scholarly journals Multiuser Scheduling In 3GPP LTE-A Uplink Non-Stand-Alone Cellular Network With Virtual MIMO

2021 ◽  
Author(s):  
Shweta Kukade ◽  
M. S. Sutaone ◽  
R. A. Patil
Keyword(s):  
Spectral Efficiency ◽  
Cellular Network ◽  
Mimo System ◽  
Scheduling Algorithm ◽  
High Volume ◽  
User Scheduling ◽  
Time Frequency ◽  
3Gpp Lte ◽  
Effective Manner ◽  
Multiuser Scheduling

Abstract New 5G architecture gives access to New Radio (NR) with co-exist LTE. 3GPP LTE-A transition towards NR is a wireless technology that is widely employed in the cellular mobile network to support significantly high volume traffic. In this paper, we propose the best N-subset reduction and a modified RME algorithm (BNSRME) as an uplink multiuser scheduler. It is responsible for allocating resources among the active users in the most effective manner. The N-subset reduction method selects the best chunk of continuous resource blocks from the available system bandwidth. Users are assigned chunks based on channel-dependent selection and utility function. The BNSRME scheduling algorithm aims to optimize performance, spectral efficiency, and allows multiuser scheduling where multiple active users are allocated the same time-frequency resources. We consider the threshold cap SNRT to improve sensitivity quality for satisfactory users. The approach is MU scheduling which will be the most commonly deployed in non-stand-alone (NSA) 5G uplink cellular network. The result shows that the system spectral efficiency improves by 32.55 % by using the proposed multiuser algorithm compared to single user scheduling in an uplink. It has been shown that its performance can be further improved by using the MU-MIMO system.

A Fast Scheduling Algorithm for Multiple User MIMO-MRC System

2013 ◽  
Vol 385-386 ◽  
pp. 1738-1742
Author(s):  
Dong Tang ◽  
Ming Xia Lv
Keyword(s):  
Computational Complexity ◽  
Mimo System ◽  
Scheduling Algorithm ◽  
Low Complexity ◽  
Base Station ◽  
User Group ◽  
User Scheduling ◽  
Channel Quality ◽  
Multiple User ◽  
The Cost

When multiple users share the same channel at one time, the total throughput of the communication system can be maximized by allocating the common radio resource to the user or the user group having the best channel quality at a given time and the multiuser diversity gain can be obtained. The object to select the users in the best group is to select the users with the maximum sum capacity. Because of the co-channel interferences among the users, user in the best group is often not the user with the best channel quality when only does it transmit to the base station. As for a scheduling algorithm, exhaustive algorithm is to search the whole possibilities of the user group and is an approach that can get the largest capability of the system by multi-user scheduling. However, this algorithm is quite complex and usually brings huge workload to a base station with multiple antennas, hence the cost of operation to a base station has substantially increased. We propose a fast user selection algorithm with low complexity to reduce the computational complexity of the scheduling algorithm. From the simulation results, this algorithm not only decreases the computational complexity of the scheduling algorithm but also retains large capability of the MIMO system.

scholarly journals Design, Analysis of 4×4 and 8×8 MIMO System with ZF, MMSE and BF Techniques

2017 ◽  
Vol 17 (2) ◽  
pp. 16-19 ◽  
Author(s):  
Arun Kumar ◽  
Piyush Vardhan ◽  
Manisha Gupta
Keyword(s):  
Signal Detection ◽  
Mimo System ◽  
Signal To Noise Ratio ◽  
Minimum Mean Square Error ◽  
Digital Signal ◽  
Base Station ◽  
Beam Forming ◽  
High Signal ◽  
Zero Forcing ◽  
Signal Processors

AbstractThis work focuses on studying signal detection using three different equalization techniques, namely: Zero Forcing (ZF), Minimum Mean Square Error (MMSE) and Beam Forming (BF), for a 4×4 MIMO-system. Results show that ZF equalization is the simplest technique for signal detection, However, Beam Forming (BF) gives better Bit Error Rate (BER) performances at high Signal to Noise Ratio (SNR) values with some complexity in design. For more antennas at the base station, it is too complex to design the weight matrix for ZF, however, it is suitable for BF with the help of good quality digital signal processors. Performance of MIMO-system, with 8 antennas at the base station using BF equalization, is analysed to get BER values at different SNR. Results show a considerable improvement in BER for 8 antennas at the base station.

scholarly journals Measured Performance Comparisons between Spatial Multiplexing and Beamforming Arrays in the 28 GHz Band

2017 ◽  
Vol 2017 ◽  
pp. 1-9
Author(s):  
Dazhi Piao ◽  
Xingning Jia ◽  
Xiaochuan Ma ◽  
Qingxin Guo ◽  
Zengrui Li
Keyword(s):  
Mimo System ◽  
Signal To Noise Ratio ◽  
Ergodic Capacity ◽  
High Gain ◽  
Spatial Multiplexing ◽  
Robust Performance ◽  
Signal To Noise ◽  
Channel Matrix ◽  
Capacity Gain ◽  
Communication Distance

A spatial multiplexing (SM) array and a beamforming (BF) array with similar antenna size working at 28 GHz are designed and fabricated. In the SM array, a 4 × 4 MIMO system is realized with each port composed of a four-element subarray. In the BF array, the whole 16 elements are used to formulate a high-gain array. The measured S-parameters are in agreement with the simulated results. For both arrays, the channel capacities are computed by the measured channel matrix and signal-to-noise ratio (SNR) in an office room. Results show that capacity of the SM system is larger than that of the BF system, although the gain of BF array is about 5 dB larger than that of the SM array. However, the capacity of the SM array depends heavily on SNR; specifically, for the 1 dBm transmit power, communication distance R=25 cm, the ergodic capacity of the SM system is 2.76 times that of the BF system, and if R=250 cm, the capacity gain is reduced to 1.45. Furthermore, compared with the BF array, the SM array has a more robust performance over antenna misalignment, because of the wider beamwidth.

scholarly journals Zero-Forcing Precoding in the Measured Massive MIMO Downlink: How Many Antennas Are Needed?

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Zhe Zheng ◽  
Jianhua Zhang ◽  
Xiaoyong Wu ◽  
Danpu Liu ◽  
Lei Tian
Keyword(s):  
Massive Mimo ◽  
Mimo System ◽  
Signal To Noise Ratio ◽  
Base Station ◽  
Simple Expression ◽  
Mimo Channel ◽  
Channel Measurements ◽  
Zero Forcing ◽  
Theoretical Derivation ◽  
Mimo Downlink

In order to understand how many antennas are needed in a multiuser massive MIMO system, theoretical derivation and channel measurements are conducted; the effect of a finite number of base station (BS) antennas on the performance capability of Zero-forcing (ZF) precoding in a rich scattering channel is quantified. Through the theoretical analysis, the needed number of the transmit antennas for ZF precoder to achieve a certain percentage of the broadcast channel (BC) capacity will monotonically decrease with the increase of the transmit signal-to-noise ratio (SNR), and the lower bound of the needed transmit antennas is derived with a simple expression. Then the theoretical derivation is verified by simulation results, and the transmission performance is evaluated by channel measurements in urban microcell (UMi) scenario with frequencies of 3.5 and 6 GHz. From the measurement results, the ZF capability can be enhanced by improving the SNR and enlarging the antenna array spacing when the massive MIMO channel does not under a favorable propagation condition. Furthermore, because of the lower spatial correlation, the performance of ZF precoding at 6 GHz is closer to the theoretical derivation than 3.5 GHz.

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