Optimal Detection of data symbol in UDMT Massive MIMO 5G System model for high spectral efficiency and energy efficiency

2021 ◽  
Author(s):  
Apoorva Vishwakarma ◽  
Devendra Kumar Meda
Keyword(s):  
Energy Efficiency ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
System Model ◽  
Optimal Detection ◽  
High Spectral Efficiency ◽  
Data Symbol

scholarly journals Energy Efficiency and Spectral Efficiency Tradeoff in Massive MIMO Multicast Transmission with Statistical CSI

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 1045
Author(s):  
Bin Jiang ◽  
Bowen Ren ◽  
Yufei Huang ◽  
Tingting Chen ◽  
Li You ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Communication Systems ◽  
Multicast Transmission ◽  
Transmission Strategy ◽  
Trade Offs ◽  
Core Technology ◽  
System Resource

As the core technology of 5G mobile communication systems, massive multi-input multi-output (MIMO) can dramatically enhance the energy efficiency (EE), as well as the spectral efficiency (SE), which meets the requirements of new applications. Meanwhile, physical layer multicast technology has gradually become the focus of next-generation communication technology research due to its capacity to efficiently provide wireless transmission from point to multipoint. The availability of channel state information (CSI), to a large extent, determines the performance of massive MIMO. However, because obtaining the perfect instantaneous CSI in massive MIMO is quite challenging, it is reasonable and practical to design a massive MIMO multicast transmission strategy using statistical CSI. In this paper, in order to optimize the system resource efficiency (RE) to achieve EE-SE balance, the EE-SE trade-offs in the massive MIMO multicast transmission are investigated with statistical CSI. Firstly, we formulate the eigenvectors of the RE optimization multicast covariance matrices of different user terminals in closed form, which illustrates that in the massive MIMO downlink, optimal RE multicast precoding is supposed to be done in the beam domain. On the basis of this viewpoint, the optimal RE precoding design is simplified into a resource efficient power allocation problem. Via invoking the quadratic transform, we propose an iterative power allocation algorithm, which obtains an adjustable and reasonable EE-SE tradeoff. Numerical simulation results reveal the near-optimal performance and the effectiveness of our proposed statistical CSI-assisted RE maximization in massive MIMO.

scholarly journals Hardware Phase Shift Hybrid Precoding Designs For Multi-User Massive MIMO Systems

2021 ◽  
Vol 2134 (1) ◽  
pp. 012027
Author(s):  
H Ayad ◽  
M Y Bendimerad ◽  
F T Bendimerad
Keyword(s):  
Spectral Efficiency ◽  
Massive Mimo ◽  
Phase Shifter ◽  
Mimo Systems ◽  
Digital Processing ◽  
Hybrid Precoding ◽  
Double Phase ◽  
High Spectral Efficiency ◽  
Fixed Phase ◽  
Configuration Simulation

Abstract Hybrid precoding is a challenging design for massive MIMO systems that involves a combination of analog and digital processing, aiming to maximize the spectral efficiency (SE). Most works on hybrid precoding focus on the single phase shifter (SPS) implementation to adapt the phase from RF chains to antennas. In this paper we propose to develop the double phase shifter (DPS) and the fixed phase shifter (FPS) in both single-path and multi-path configuration. Simulation results certify a significant improvement for both proposed implementations with high hardware efficiency (HE) and high spectral efficiency especially in multi-path environment.

scholarly journals Densely Deployed Indoor Massive MIMO Experiment: From Small Cells to Spectrum Sharing to Cooperation

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4346
Author(s):  
Andrea P. Guevara ◽  
Sofie Pollin
Keyword(s):  
Spectral Efficiency ◽  
Interference Cancellation ◽  
Massive Mimo ◽  
Spectrum Sharing ◽  
Interference Suppression ◽  
Computational Cost ◽  
Small Cells ◽  
Optimal Capacity ◽  
High Spectral Efficiency ◽  
The Impact

Massive MIMO is a key 5G technology that achieves high spectral efficiency and capacity by significantly increasing the number of antennas per cell. Furthermore, due to precoding, massive MIMO allows co-channel interference cancellation across cells. In this work, based on experimental channel data for an indoor scenario, we analyse the impact of inter and intra-cell interference suppression in terms of spectral efficiency, capacity, user fairness and computational cost for three simulated systems under different cooperation levels. The first scenario assumes a cooperative case where eight neighbouring cells share the spectrum and infrastructure. This scenario provides the highest system performance; however, user fairness is achieved only when there is inter and intra-cell interference suppression. The second scenario considers eight cells that only share the spectrum; with full intra-cell and inter-cell interference cancellation, it is possible to achieve 32% of the optimal capacity with 20% of the computational cost in each distributed CPU, although the total computational cost per system is the highest. The third scenario considers eight independent cells operating in different frequency bands; in this case, intra-cell interference suppression leads to higher spectral efficiency compared to the cooperative case without intra-cell interference suppression.

scholarly journals Energy Efficiency Optimization in Adaptive Massive MIMO Networks for 5G Applications Using Genetic Algorithm

2021 ◽  
Author(s):  
Ibrahim Salah ◽  
M. Mourad Mabrook ◽  
Kamel Hussein Rahouma ◽  
Aziza I. Hussein
Keyword(s):  
Genetic Algorithm ◽  
Energy Efficiency ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Mimo System ◽  
Optimization Technique ◽  
Base Station ◽  
Maximum Efficiency ◽  
Adaptive Optimization ◽  
Trade Offs

Abstract Given that the exponential pace of growth in wireless traffic has continued for more than a century, wireless communication is one of the most influential innovations in recent years. Massive Multiple-Input Multiple-Output (M-MIMO) is a promising technology for meeting the world's exponential growth in mobile data traffic, particularly in 5G networks. The most critical metrics in the massive MIMO scheme are Spectral Efficiency (SE) and Energy Efficiency (EE). For single-cell MMIMO uplink transmission, energy and spectral-efficiency trade-offs have to be estimated by optimizing the number of base station antennas versus the number of active users. This paper proposes an adaptive optimization technique focusing on maximizing Energy Efficiency at full spectral efficiency using a Genetic Algorithm (GA) optimizer. The number of active antennas is estimated according to the change in the number of active users based on the proposed GA scheme that optimizes the EE in the M-MIMO system. Simulation results show that the GA optimization technique achieved the maximum energy efficiency of the 5G M-MIMO platform and the maximum efficiency in the trade-off process.

Area Spectral Efficiency and Area Energy Efficiency of Massive MIMO Cellular Systems

2016 ◽  
Vol 65 (5) ◽  
pp. 3243-3254 ◽  
Author(s):  
Yuanxue Xin ◽  
Dongming Wang ◽  
Jiamin Li ◽  
Huilin Zhu ◽  
Jiangzhou Wang ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Cellular Systems ◽  
Area Spectral Efficiency
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