An Efficient Precoding Algorithm for mmWave Massive MIMO Systems

Khan, Imran; Henna, Shagufta; Anjum, Nasreen; Sali, Aduwati; Rodrigues, Joel J. P. C.; Khan, Yousaf; Khattak, Muhammad Irfan; Altaf, Farhan

doi:10.3390/sym11091099

Cited by 8 publications

(7 citation statements)

References 25 publications

(39 reference statements)

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“…From the results, the performance is similar to the orthogonal matching pursuit, which costs much fewer complexities than the orthogonal matching pursuit. Another low complexity hybrid mmWave massive MIMO precoding scheme to overcome the complexity of orthogonal matching pursuit is investigated in [12]. A bird swarm algorithm with matrixinversion is designed to obtain the global optimum value with high search.…”

Section: A Prior Workmentioning

confidence: 99%

Performance Enhancement of MmWave MIMO Systems Using Deep Learning Framework

2021

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In order to obtain beamforming gains and prevent high pathloss in millimeter wave (mmWave) systems, large number of antennas is employed. Digital precoders are difficult to implement with many antennas because of hardware constraints, while analog precoders have limited performance. In this paper, hybrid precoding based on a deep learning framework, HybridPrecodingNet, is proposed, which uses largescale information to predict the parameters of hybrid precoders and decoders. The statistics of the channel covariance matrix are applied to design the hybrid precoders and decoders. The proposed HybridPrecodingNet at the receiver is applied for the channel estimation and design of hybrid decoders. In our proposed framework, the structure of HybridPrecodingNet is trained to learn how to optimize the hybrid precoder and decoder for maximum spectral efficiency. Comparison between different precoding techniques is provided. Results show that HybridPrecodingNet approaches the sub-optimal solution and gives significant spectral efficiency enhancement.

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Section: A Prior Workmentioning

confidence: 99%

Performance Enhancement of MmWave MIMO Systems Using Deep Learning Framework

2021

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“…The objective function was discussed f aximum harvested power and was searched by evolution algorithms. In our research, the objectiv nction was the inverse of the energy efficiency in Equation (14), and the number of generatio as set to 600. In other words, when the generation reached 600, the algorithm will be terminate e relative parameters for SADDE and APSO are as following: population size is 30 and crossov obability is 0.8.…”

Section: Environment Settingsmentioning

confidence: 99%

“…However, the study only used an analytic solution to calculate the bit error rate (BER) with a statistical channel. In the work of [14], precoding optimization research reduced the resources required for computing, but energy was not taken into consideration.…”

Section: Introductionmentioning

confidence: 99%

Theoretical Derivation and Optimization Verification of BER for Indoor SWIPT Environments

et al. 2020

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Symmetrical antenna array is useful for omni bearing beamforming adjustment with multiple receivers. Beam-forming techniques using evolution algorithms have been studied for multi-user resource allocation in simultaneous wireless information and power transfer (SWIPT) systems. In a high-capacity broadband communication system there are many users with wearable devices. A transmitter provides simultaneous wireless information and power to a particular receiver, and the other receivers harvest energy from the radio frequency while being idle. In addition, the ray bounce tracking method is used to estimate the multi-path channel, and the Fourier method is used to perform the time domain conversion. A simple method for reducing the frequency selective effort of the multiple channels using the feed line length instead of the digital phase shifts is proposed. The feed line length and excitation current of the transmitting antennas are adjusted to maximize the energy harvest efficiency under the bit error rate (BER) constraint. We use the time-domain multipath signal to calculate the BER, which includes the inter symbol interference for the wideband system. In addition, we use multi-objective function for optimization. To the best of our knowledge, resource allocation algorithms for this problem have not been reported in the literature. The optimal radiation patterns are synthesized by the asynchronous particle swarm optimization (APSO) and self-adaptive dynamic differential evolution (SADDE) algorithms. Both APSO and SADDE can form good patterns for the receiver for energy harvesting. However, APSO has a faster convergence speed than SADDE.

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“…In this section, we briefly review the state-of-the-art on hybrid analog-digital architectures. Namely, beamforming approaches designed for narrowband single-user mmWave communications systems have been proposed in [11][12][13]. Particularly, the authors of [11] designed a bird swarm algorithm based on a matrix-inversion bypass precoder algorithm to overcome the large complexity of orthogonal matching pursuit method, namely the implicit matrix inversion.…”

Section: Introductionmentioning

confidence: 99%

“…Namely, beamforming approaches designed for narrowband single-user mmWave communications systems have been proposed in [11][12][13]. Particularly, the authors of [11] designed a bird swarm algorithm based on a matrix-inversion bypass precoder algorithm to overcome the large complexity of orthogonal matching pursuit method, namely the implicit matrix inversion. In [12], a general solution for single user narrowband systems was proposed to convert any existing precoder/combiner designed for the full digital structure into an analog-digital precoder/combiner for the hybrid structure.…”

Section: Introductionmentioning

confidence: 99%

Iterative Analog–Digital Multi-User Equalizer for Wideband Millimeter Wave Massive MIMO Systems

Magueta

Castanheira

Pedrosa

et al. 2020

Sensors

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Most of the previous work on hybrid transmit and receive beamforming focused on narrowband channels. Because the millimeter wave channels are expected to be wideband, it is crucial to propose efficient solutions for frequency-selective channels. In this regard, this paper proposes an iterative analog–digital multi-user equalizer scheme for the uplink of wideband millimeter-wave massive multiple-input-multiple-output (MIMO) systems. By iterative equalizer we mean that both analog and digital parts are updated using as input the estimates obtained at the previous iteration. The proposed iterative analog–digital multi-user equalizer is designed by minimizing the sum of the mean square error of the data estimates over the subcarriers. We assume that the analog part is fixed for all subcarriers while the digital part is computed on a per subcarrier basis. Due to the complexity of the resulting optimization problem, a sequential approach is proposed to compute the analog phase shifters values for each radio frequency (RF) chain. We also derive an accurate, semi-analytical approach for obtaining the bit error rate (BER) of the proposed hybrid system. The proposed solution is compared with other hybrid equalizer schemes, recently designed for wideband millimeter-wave (mmWave) massive MIMO systems. The simulation results show that the performance of the developed analog–digital multi-user equalizer is close to full-digital counterpart and outperforms the previous hybrid approach.

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An Efficient Precoding Algorithm for mmWave Massive MIMO Systems

Cited by 8 publications

References 25 publications

Performance Enhancement of MmWave MIMO Systems Using Deep Learning Framework

Performance Enhancement of MmWave MIMO Systems Using Deep Learning Framework

Theoretical Derivation and Optimization Verification of BER for Indoor SWIPT Environments

Iterative Analog–Digital Multi-User Equalizer for Wideband Millimeter Wave Massive MIMO Systems

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