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1. Multi-level Polar Coded Modulation for the Decode-Forward Relay Channel

   https://doi.org/10.1109/GLOBECOM46510.2021.9685422  

   Wan, Heping ; Nosratinia, Aria ( December 2021 , IEEE Global Communications Conference (GLOBECOM))

   We investigate the performance of multi-level polar coded modulation in the decode-forward relay channel. We begin by numerically analyzing the rates assigned to polar codes of all levels via chain rule and error exponent. The construction of polar codes follows the 5G standard. A joint decoding based on maximum ratio combining with multistage decoding is proposed for the destination. We simulate the error performance under 16QAM with gray labeling and Ungerboeck's set partitioning. In the half-duplex mode, a gain of 2.5dB is observed compared with the state of the art, consisting of 0.7 dB gain due to multistage decoding and 1.8dB gain due to the choice of labeling. In addition, the error performance according to error exponent is compared with the chain rule. A dispersion bound for the decode-forward relaying is calculated. 

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2. Hybrid Precoding/Combining Design in mmWaveAmplify-and-Forward MIMO Relay Networks

   Jiang, L. ; Liu, X. ; Jafarkhani, H. ( May 2019 , IEEE International Conference on Communications)

   In this paper, we consider the amplify-and-forward relay networks in mmWave systems and propose a hybrid precoder/combiner design approach. The phase-only RF precoding/ combining matrices are first designed to support multi-stream transmission, where we compensate the phase for the eigenmodes of the channel. Then, the baseband precoders/combiners are performed to achieve the maximum mutual information. Based on the data processing inequality for the mutual information, we first jointly design the baseband source and relay nodes to maximize the mutual information before the destination baseband receiver. The proposed low-complexity iterative algorithm for the source and relay nodes is based on the equivalence between mutual information maximization and the weighted MMSE. After we obtain the optimal precoder and combiner for the source and relay nodes, we implement the MMSE-SIC filter at the baseband receiver to keep the mutual information unchanged, thus obtaining the optimal mutual information for the whole relay system. Simulation results show that our algorithm achieves better performance with lower complexity compared with other algorithms in the literature. 

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3. Neural Network-based Channel Estimation for 2x2 and 4x4 MIMO Communication in Noisy Channels

   Yang, Kanghyeok ; Vuran, Mehmet C. ; Scott, Stephen ; Guo, Fujuan ; Ahn, Changbum R. ( May 2018 , International Balkan Conference on Communications and Networking)

   With increasing needs of fast and reliable commu- nication between devices, wireless communication techniques are rapidly evolving to meet such needs. Multiple input and output (MIMO) systems are one of the key techniques that utilize multiple antennas for high-throughput and reliable communication. However, increasing the number of antennas in communication also adds to the complexity of channel esti- mation, which is essential to accurately decode the transmitted data. Therefore, development of accurate and efficient channel estimation methods is necessary. We report the performance of machine learning-based channel estimation approaches to enhance channel estimation performance in high-noise envi- ronments. More specifically, bit error rate (BER) performance of 2 × 2 and 4 × 4 MIMO communication systems with space- time block coding model (STBC) and two neural network-based channel estimation algorithms is analyzed. Most significantly, the results demonstrate that a generalized regression neural network (GRNN) model matches BER results of a known-channel communication for 4 × 4 MIMO with 8-bit pilots, when trained in a specific signal to noise ratio (SNR) regime. Moreover, up to 9dB improvement in signal-to-noise ratio (SNR) for a target BER is observed, compared to least square (LS) channel estimation, especially when the model is trained in the low SNR regime. A deep artificial neural network (Deep ANN) model shows worse BER performance compared to LS in all tested environments. These preliminary results present an opportunity for achieving better performance in channel estimation through GRNN and highlight further research topics for deployment in the wild. 

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4. Coverage Analysis of Relay Assisted Millimeter Wave Cellular Networks with Spatial Correlation

   https://doi.org/10.1109/WCNC45663.2020.9120776  

   Xu, Simin ; Yang, Nan ; He, Biao ; Jafarkhani, Hamid ( May 2020 , IEEE Wireless Communications and Networking Conference (WCNC-20))

   We propose a novel analytical framework for evaluating the coverage performance of a millimeter wave (mmWave) cellular network where idle user equipments (UEs) act as relays. In this network, the base station (BS) adopts either the direct mode to transmit to the destination UE, or the relay mode if the direct mode fails, where the BS transmits to the relay UE and then the relay UE transmits to the destination UE. To address the drastic rotational movements of destination UEs in practice, we propose to adopt selection combining at destination UEs. New expression is derived for the signal-to-interference-plus-noise ratio (SINR) coverage probability of the network. Using numerical results, we first demonstrate the accuracy of our new expression. Then we show that ignoring spatial correlation, which has been commonly adopted in the literature, leads to severe over estimation of the SINR coverage probability. Furthermore, we show that introducing relays into a mmWave cellular network vastly improves the coverage performance. In addition, we show that the optimal BS density maximizing the SINR coverage probability can be determined by using our analysis. 

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5. Kramers–Kronig detection of four 20  Gbaud 16-QAM channels using Kerr combs for a shared phase estimation

   https://doi.org/10.1364/OL.387360  

   Zou, Kaiheng ; Liao, Peicheng ; Cao, Yinwen ; Kordts, Arne ; Almaiman, Ahmed ; Karpov, Maxim ; Pfeiffer, Martin_Hubert_Peter ; Alishahi, Fatemeh ; Fallahpour, Ahmad ; Tur, Moshe ; et al ( March 2020 , Optics Letters)

   We experimentally demonstrate Kramers–Kronig detection of four 20 Gbaud 16-quadrature-amplitude-modulated (QAM) channels after 50 km fiber transmission using two soliton Kerr combs as signal sources and local oscillators. The estimated carrier phase at the receiver for each of the channels is relatively similar due to the coherence between the frequency comb lines. The standard deviation of the estimated carrier phase difference of the channels is less than 0.08 rad after 50 km single-mode fiber (SMF) transmission. This enables the carrier phase recovery derived from one channel to be shared among multiple channels. In the back-to-back scenario, the bit error rate (BER) performance for shared carrier phase recovery shows an optical signal-to-noise ratio penalty of$\sim <\#comment/>0.5\mathrm{d}\mathrm{B}$compared to the BER performance for carrier phase recovery when derived for each channel independently. BERs below the forward error correction threshold are achieved after 50 km SMF transmission with both independent and shared carrier phase recovery for four 20-Gbaud 16-QAM signals.

    

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