To harvest the multiplexing and beamforming gains of these large-scale MIMO systems, however, the channel knowledge needs to be acquired at the massive MIMO transmitters. N2 - Massive MIMO is a key component of current and future wireless communication systems. ACKNOWLEDGMENT This work has been supported in part by the NSF IRES award 1854273 and the NSF SenSIP/NCSS award 1540040. T2 - 54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020 In addition, we can see that the ELM receiver with circulant input weight matrix delivers almost the same performance as the conventional ELM based one, but with much lower complexity (the complexity of the latter is 3.6 times of that of the former).T1 - Deep Learning Based MIMO Channel Prediction In contrast, the two ELM based receivers work much better than the receivers with LMMSE and ZF followed by the postdistorter, which indicates that the ELM based receivers can more efficiently handle the cross-LED interference and LED nonlinearity. It can be seen that the LMMSE and ZF receivers simply do not work properly due to the nonlinearity distortion.
#Deep learning based mimo communications how to#
We note that the LMMSE and ZF receivers are designed with the exact knowledge of channel matrix H because it is unknown how to estimate H without knowing the LED nonlinearity, or vice versa. For comparison, we also show the performance of the LMMSE (linear minimum mean square error) and ZF (zero forcing) receivers which simply ignore the nonlinearity of the LEDs, and the performance of the receivers with LMMSE and ZF (to deal with cross-LED interference) followed by a polynomial based postdistorter (to deal with LED nonlinearity). To the best of our knowledge, this is the first work to deal with LED nonlinearity and cross-LED interference in LED MIMO communications.įigure 4 shows the symbol error rate (SER) performance of various receivers, where the signal-to-noise ratio (SNR) is defined as the ratio of the average power of the received electrical signal at the PDs to the power of noise. The results show that the proposed receiver can much more efficiently handle the LED nonlinearity and cross-LED interference and bring significant performance gain. The proposed ELM-based receiver is compared with the receivers where the MIMO channel matrix is assumed to be known and LED nonlinearity and cross-LED interference are handled separately. To achieve low complexity, we propose to use circulant input weight matrix in our ELM-based receiver, which enables the use of the fast Fourier transform (FFT) to tackle the most computational intensive part of the receiver, leading to an efficient receiver while with negligible performance loss compared to the receiver based on the original ELM. In particular, we employ the extreme learning machine (ELM) due to its fast learning speed. In this work, we propose to use the neural networks to handle them jointly. However, as the received signal includes the distortion due to both LED nonlinearity and cross-LED interference, it is difficult to estimate the MIMO channel matrix and LED nonlinearity without knowing each other. A receiver may be designed by dealing with the nonlinearity and cross-LED interference separately. In LED MIMO, the receiver needs to handle both LED nonlinearity and cross-LED interference properly. A variety of optical MIMO techniques have been studied in. Hence, multiple input multiple output (MIMO) techniques, where multiple LEDs and photodiodes (PDs) are equipped at the transmitter and receiver, respectively, are employed to achieve high data rate transmission as well as sufficient illumination. Meanwhile, a single LED may not provide sufficient illumination for indoor lighting.
However, transmission with high data rate is challenging due to the low modulation bandwidth of LEDs, despite the wide terahertz visible light spectrum. In addition, the spectrum region of visible light is unregulated and interferences with radio bands can be avoided, and it is easy to achieve secure transmission within a certain space and prevent interferences from other places. As light emitting diodes (LEDs) can be used for simultaneous illumination and data transmission due to their fast switching capability, LED communication has received tremendous attention recently.
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