Massive-Multiple Inputs and Multiple Outputs (M-MIMO) is considered as one of the standard techniques in improving the performance of Fifth Generation (5G) radio. 5G signal detection with low propagation delay and high throughput with minimum computational intricacy are some of the serious concerns in the deployment of 5G. The evaluation of 5G promises a high quality of service (QoS), a high data rate, low latency, and spectral efficiency, ensuring several applications that will improve the services in every sector. The existing detection techniques cannot be utilised in 5G and beyond 5G due to the high complexity issues in their implementation. In the proposed article, the Approximation Message Passing (AMP) is implemented and compared with the existing Minimum Mean Square Error (MMSE) and Message Passing Detector (MPD) algorithms. The outcomes of the work show that the performance of Bit Error Rate (BER) is improved with minimal complexity.

In the present scenario, it is seen that the data traffic is increasing day by day. In the year 2025, it is estimated that data traffic will increase by 30% [

In recent years, several detection algorithms such as Minimum Mean Square Error (MMSE), Zero Forcing Equalizer (ZFE), and Maximum Likelihood (ML) have been proposed. The ML is regarded as one of the most efficient detection methods [

In this work, we studied the performance of the novel AMP algorithm and conventional detection schemes on non-orthogonal multiple access waveforms in the Rician channel.

The various parameters such as BER and Peak to Average Power Ratio (PAPR) are estimated and compared with the conventional detection algorithms.

We introduced a novel 5G signal detection algorithm based on the combination of detection schemes. The key objective of the designed algorithm is to reduce the propagation delay and complexity with minimal degradation of the BER performance.

The conventional PAPR methods have been successfully reducing the PAPR but the complexity is also increasing, which has been significantly achieved in the presented article.

The detection of M-MIMO signals is considered a critical task as it involves the number of signals received at the receiver and the complexity is extensively increased. The throughput of the MIMO is compromised to obtain a low-complexity M-MIMO framework and vice versa. The arrangement of conventional M-MIMO is shown in

The conventional M-MIMO signai is given by:

At this stage, we are generating a phase factor (

The phase weighting factor can be expressed as:

The modulated signal (

In order to reduce the amplitude and phase error, the MIMO modulated symbol is weighted by phase factor:

The

An Inverse Fast Fourier Transform (IFFT) is applied to the

The PAPR of M-MIMO can be estimated as:

The received signal (Z) considering the noise (N) and channel response (h) is given by:

In AMP, the messages are linked with the code, which significantly decreases the quantity of messages in a significant manner due to the computational complexity being reduced. The AMP was initially designed to estimate the signal correction and resolve the selection issues in the digital processing framework. The AMP detector has grown in popularity due to its ability to reduce complexity while increasing framework throughput. The AMP gave an efficient performance, and it is easy to design for massive framework dimensions. Hence, AMP is efficiently utilised in linear evaluation of M-MIMO structure, encoding, and multi-signal detection. It is also seen that the concurrency rate of the AMP is extremely good. However, the concurrence rate degrades for highly complex systems. The efficiency of the Message Passing Detector (MPD) is further enhanced by utilising the channel hardening hypothesis, which results in a simple estimation of the Gram Matrix determination. Further, the throughput performance of the MPD is better than the MMSE due to the fact that the matrix inversion is not required in the MPD. However, it is seen that the complexity of the MPD increases due to the large number of exponential calculations [

In AMP, the error is reduced and efficient signal detection is carried out by utilising the repetitive threshold technique, given as:

The conventional representation of the transmit (y) and receive signal (z) is given by [

The characteristics of the channel can be written as:

The rank (r) of the channel is given by [

The signal at the receiver is given by:

The representation of the channel with QRM is estimated as:

In

The conventional M-MIMO is given by:

The signal estimated by the proposed algorithm is given by:

The detection of the 5G signal by the multiple antennas is given by:

The estimation of the BER is given below:

Step 5: The power of the transmitted signal is (

The primary objective of the proposed article is to investigate the performance of AMP for 32 × 32 MIMO and 64 × 64 MIMO structures. The 64-QAM transmission scheme and rician channel are selected for our analysis. The FFT size is 64 and number of sub-carriers is selected as 64, over sampling is 4, iteration perform is 50 with coding rate (1/16) and constraint length (8). Matlab-2014 is utilised to simulate the AMP algorithms for M-MIMO structures. The BER of the 32 × 32 MIMO structure for the AMP algorithm is given in ^{−3} is obtained at the SNR of 6.2, 9.1 and 10.2 dB for AMP, MPD, and MMSE. It is seen that the proposed AMP obtained a gain of 3.2 and 4 dB as compared with the detection method mentioned above. It is also seen that the complexity of the proposed AMP is low due to the non-utilization of matrix inversion. Hence, it is concluded that the proposed AMP outperforms the MPD and MMSE detection algorithms.

To further evaluate the performance of the proposed AMP, the 64 × 64 MIMO structure is simulated and the AMP is applied to detect the signal. The BER curve, given in

PAPR is considered a significant problem in multicarrier waveforms. In ^{−3}, the PAPR of 32 × 32 and 64 × 64 MIMO is 9 and 5.2 dB. Hence, it is concluded that the throughput of the system is enhanced with an increasing number of antennas, but the complexity of the structure also increases with the size of the MIMO structure.

In this work, we define number of additions and multiplications as the complexity of the algorithms.

S. No | Algorithms | Additions |
---|---|---|

1 | MMSE | |

2 | MPD | |

3 | Proposed work | LM |

The utilisation of M-MIMO structures efficiently improves the throughput of the 5G and beyond 5G frameworks. However, the detection of the signal is complicated due to the utilisation of the several numbers of antennas at the BS. Advanced detection algorithms in 5G radio will ensure efficient performance and service quality. However, the existing detection schemes are not suitable for the advanced waveforms. In this paper, we present an advanced AMP algorithm for M-MIMO structures. It is seen that the proposed AMP algorithm gives an efficient BER performance and complexity is also reduced as compared with the MMSE and MDP algorithms. However, it is noted that the PAPR is one of the significant advanced waveforms proposed for 5G radio. The simulation results reveal that the PAPR is high in 64 × 64 MIMO as compared with 32 × 32. It is also suggested that suitable PAPR algorithms be used at the transmitting portion of the 5G radio to reduce the PAPR, which can further increase the complexity of the schemes.

The authors extend their appreciation to Taif University Researchers Supporting Project Number (TURSP-2020/98) Taif University, Taif, Saudi Arabia.