Spectral- and Energy-Efficiency of Multi-Pair Two-Way Massive MIMO Relay Systems Experiencing Channel Aging

Li, Lixin; He, Jiao; Yang, Lie‐Liang; Han, Zhu; Pan, Miao; Chen, Wei; Zhang, Huisheng; Xu, Li

doi:10.1109/access.2019.2908882

Cited by 11 publications

(10 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hyper spectral remote sensing with various wavelength bands enhances the separation in spectral classes of a different one. [19][20][21][22] Finally, the survey of various spectrum sensing techniques is analyzed, and recent advancement is discussed in Ali and Hamouda. 23 The common challenges based on existing limitation are listed below.…”

Section: Discussionmentioning

confidence: 99%

“…Li et al 19 introduced the impact of EE and also aging on the spectral. The massive antennas are organized at the relay, and the amplify protocol was embedded to the maximum ratio transmission and also the maximum ratio combining.…”

Section: Related Workmentioning

confidence: 99%

“…To identify and to detect the spectral holes and also weak signals was a major and important problem facing by CR along with the spectrum sensing. Hyper spectral remote sensing with various wavelength bands enhances the separation in spectral classes of a different one 19–22 . Finally, the survey of various spectrum sensing techniques is analyzed, and recent advancement is discussed in Ali and Hamouda 23 …”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Modified spider monkey optimization—An enhanced optimization of spectrum sharing in cognitive radio networks

Dinesh¹,

Venkatakrishnan²,

Jeyanthi

2020

Int J Communication

View full text Add to dashboard Cite

Summary At present, the demand for wireless communications is growing tremendously. Cognitive radio network plays an important role in making the spectrum to be used effectively. Uncertainty in channels and interference were generally occurs that reduced the system efficiency. To overcome the load usage problem, the proposed system of spectrum sensing and scheduling algorithms is introduced, where the available spectrums are sensed or detected and scheduled to load the free spectrum. Spectrum sensing is a cognitive radio basic function to thwart the harmful interference with licensed users and detect the available spectrum for enhancing the spectrum's utilization. In the proposed technique, initially, the spectrum sharing and sensing method is put forward to raise the throughput and quality of service necessity. At this time, spectrum sharing in common with scheduling process is presented, where the available spectrum, the load is scheduled and sensed to free the spectrum. Here, the modified spider monkey optimization (MSMO) technique is used for spectrum sensing and detecting free spectrums, thereby enhancing the energy efficiency of the available spectrum. This technique will found the optimal solution and increases the expectation of some decisions. Modified round robin algorithm is used for scheduling load. In this algorithm, every packet flow has its packet queue presented in the network interface controller. The performance analysis is finally measured using metrics such as throughput, handoff, success probability, and false alarm probability.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Modified spider monkey optimization—An enhanced optimization of spectrum sharing in cognitive radio networks

Dinesh¹,

Venkatakrishnan²,

Jeyanthi

2020

Int J Communication

View full text Add to dashboard Cite

show abstract

“…Even in relay networks with massive MIMO, the channel aging effect is also studied [11]. Considering multi‐pair two‐way massive MIMO relay systems, Li et al [12] conclude that the channel aging may significantly degrade the achievable performance in terms of spectral efficiency and energy efficiency. As a consequence, it is of much importance and worth to exploit the channel aging effect on the system performance of massive MIMO.…”

Section: Introductionmentioning

confidence: 99%

Spectral efficiency analysis of multi‐cell multi‐user massive MIMO over channel aging

et al. 2020

View full text Add to dashboard Cite

“…The mmWave massive MIMO system is capable of enhancing the spectrum efficiency (SE) by providing the large array gain [5]. However, the large-scale antennas, the highresolution analog-to-digital converters (ADCs)/digital-toanalog converters (DACs), and the fully digital precoding scheme will result in big power consumption and unfordable hardware costs.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Spectrum Efficiency Hybrid Precoding With Lens Array and Low-Resolution ADCs

Ren

et al. 2019

IEEE Access

Self Cite

View full text Add to dashboard Cite

Hybrid precoding is an important issue in millimeter wave (mmWave) massive multi-input and multi-output (MIMO) system. Specially, energy-saving hybrid precoding architectures and efficient hybrid precoding schemes provide ideas for solving this issue. In this paper, we propose a hybrid precoding/combining architecture that is low-cost and easy to implement. Specifically, a hybrid precoding architecture is realized by the lens sub-arrays at the base station (BS). Moreover, a hybrid combining architecture applies the low-resolution analog-to-digital converters (ADCs) at the front end of the radio frequency (RF) chains at the receiving terminal. Based on the hybrid precoding/combining architecture, the hybrid precoder and combiner are jointly optimized to maximize the spectrum efficiency (SE) in the downlink systems, which is a combinatorial optimization problem due to hardware constraints. The cross-entropy (CE) approach in machine learning (ML) is a simple way to solve the combinatorial optimization problem benefiting from its adaptive update procedure. Therefore, we propose an adaptive hybrid precoder/combiner design scheme (AHDS), in which a hybrid precoding algorithm based on the improved CE (ICE) inspired by ML is adopted to design the optimal hybrid precoder, and an approximate optimization method (AOM) is suggested when designing the hybrid combiner. In general, compared with the existing hybrid design schemes, the proposed AHDS is demonstrated to have significant advantage in SE with low computational complexity.INDEX TERMS Hybrid precoding, machine learning, lens sub-array, low-resolution ADC, multi-input and multi-output.

show abstract

Spectral- and Energy-Efficiency of Multi-Pair Two-Way Massive MIMO Relay Systems Experiencing Channel Aging

Cited by 11 publications

References 49 publications

Modified spider monkey optimization—An enhanced optimization of spectrum sharing in cognitive radio networks

Modified spider monkey optimization—An enhanced optimization of spectrum sharing in cognitive radio networks

Spectral efficiency analysis of multi‐cell multi‐user massive MIMO over channel aging

Machine Learning-Based Spectrum Efficiency Hybrid Precoding With Lens Array and Low-Resolution ADCs

Contact Info

Product

Resources

About