This article outlines the basic principles of OFDM-IDMA. Comparisons with other alternative technologies such as OFDM-CDMA and OFDMA are provided. Some attractive features of OFMD-IDMA are explained, including low-cost iterative multi-user detection, flexible rate adaptation, frequency diversity, and significant advantages regarding spectral and power efficiency.

Lung cancer has become one of the life-threatening killers. Lung disease need to be assisted by CT images taken doctor's diagnosis, and the segmented CT image of the lung parenchyma is the first step to help doctor diagnosis. For the problem of accurately segmenting the lung parenchyma, this paper proposes a segmentation method based on the combination of VGG-16 and dilated convolution. First of all, we use the first three parts of VGG-16 network structure to convolution and pooling the input image. Secondly, using multiple sets of dilated convolutions make the network has a large enough receptive field. Finally, the multi-scale convolution features are fused, and each pixel is predicted using MLP to segment the parenchymal region. Experimental results were produced over state of the art on 137 images which key metrics Dice similarity coefficient (DSC) is 0.9867. Experimental results show that this method can effectively segment the lung parenchymal area, and compared to other conventional methods better.

In this paper, we present an unequal power allocation technique to increase the throughput of code-division multiple-access (CDMA) systems with chip-level interleavers. Performance is optimized, respectively, based on received and transmitted power allocation. Linear programming and power matching techniques are developed to provide solutions to systems with a very large number of users. Various numerical results are provided to demonstrate the efficiency of the proposed techniques and to examine the impact of system parameters, such as iteration number and interleaver length. We also show that with some very simple forward error correction codes, such as repetition codes or convolutional codes, the proposed scheme can achieve throughput reasonably close to that predicted by theoretical limit in multiple access channels.

This paper investigates the characteristics and performance of orthogonal delay-Doppler division multiplexing (ODDM) modulation over doubly selective physical channels with general delay and Doppler . Assuming that the implementation of the ODDM is based on IDFT/DFT and sample-wise pulse shaping/receiver filtering, we study the input-output (IO) relation for ODDM and characterize the equivalent sampled delay-Doppler (ESDD) domain channel in terms of the parameters of the physical channel and the DD plane orthogonal pulse (DDOP) . The established IO relation can describe the patterns of inter-symbol-interference (ISI) and inter-carrier-interference (ICI) for more general delay and Doppler shifts of the physical channel. Based on the results, we also examine the influence of the transmitter configuration on the sparsity of the ESDD channel and on the resulting performance-complexity tradeoff of ODDM. We further introduce a pilot-assisted method of estimating the physical channel parameters by leveraging the derived IO relation and the root-MUSIC algorithm. We also present a low-complexity symbol detector for ODDM systems based on conjugate gradients (CG). Simulation results under various settings show that the error performance of ODDM based on the estimate of the physical channel approaches that with perfect channel state information (CSI) at a low-to-medium signal-to-noise ratio (SNR), but has an increased gap from the perfect CSI case when the SNR increases.

We study superposition coded modulation (SCM) with iterative linear minimum-mean-square-error (LMMSE) detection. We show that SCM offers an attractive solution for highly complicated transmission environments with severe interference. We analyze the impact of signaling schemes on the performance of iterative LMMSE detection. We prove that among all possible signaling methods, SCM maximizes the output signal-to-noise/ interference ratio (SNIR) in the LMMSE estimates during iterative detection. Numerical examples are used to demonstrate that SCM outperforms other signaling methods when iterative LMMSE detection is applied to multi-user/multi-antenna/multipath channels.

This paper studies the influence of signal detection schemes on the energy efficiency (EE) of uplink multiple-input multiple-output (MIMO) systems with low-resolution analog-to-digital converters (ADCs). Assuming equal transmission rates for all users, we derive the optimal power allocation and their analytical approximations for zero-forcing (ZF) and ZF successive interference cancellation (ZF-SIC) receivers. Both the cases with perfect channel state information (CSI) and with imperfect CSI are considered. The EE with different receivers is compared. The results indicate that for uplink massive MIMO systems with low-resolution ADCs, the radio-frequency circuit power consumption can be significant because a large number of antennas is required to compensate for the loss due to quantization errors while the number of base station antennas needed with the ZF-SIC receiver is significantly smaller than that with the ZF receiver. Meanwhile, the increase of power consumption of signal processing with ZF-SIC can be moderate, due to the fact that the receiver weights are reused in a coherent block and the dimensionality is reduced. Consequently, the ZF-SIC receiver is able to improve the overall EE for massive MIMO systems with practical ADCs. We also conduct an approximation analysis for a multi-cell scenario with the pilot contamination and inter-cell-interference considered.