Clipping noise estimation and cancellation are essential in orthogonal frequency division multiplexing (OFDM) systems when clipping is performed to reduce the peak-to-average power ratio (PAPR). Motivated by the richer representational capacity of complex numbers and the fact that communication is a complex-valued problem, a novel clipping noise estimation scheme based on deep complex neural network is proposed in this paper. Specifically, the clipping noise is determined by a deep complex network, namely clipping noise estimation network (CNE-Net), such that the mean square error (MSE) and the sparsity of the estimated clipping noise are jointly optimized. Besides, an ordering based zero-forcing scheme is utilized to further ensure the sparsity of the estimated clipping noise. Simulation results show that the proposed CNE-Net shows comparable performance with the conventional decision-aided reconstruction (DAR) scheme and can achieve better performance than the one-iteration DAR scheme when the clipping noise is not sparse enough. In summary, the CNE-Net has a good capability to estimate the clipping noise from noise-affected features.

For OFDM systems, to cope with the remain problems of high complexity and low performance in conventional clipping noise cancellation methods, a robust scheme based on location-aware compressed sensing (CS) and phase correction is proposed in this paper. Based on CS theory, a simple and configurable selection criterion is utilized to choose reliable observations for the clipping noise reconstruction. The transceiver is redesigned to transmit both the data and the clipping location. With the aid of clipping location information and phase information from the receiver, the proposed scheme improves both the accuracy and computational complexity. Simulation results show that the proposed scheme achieves excellent performance even in low signal-to-noise ratio (SNR) environments. Besides, due to the low computational complexity and excellent adaptivity, the proposed scheme is more feasible in practical engineering applications than other CS-based methods.

Recently, mobile ad-hoc networks (MANET) have been widely used in several scenarios. Due to its generally high demands on clock synchronization accuracy, the conventional synchronization algorithms cannot be applied in many high-speed MANET applications. Hence, in this paper, a clock synchronization algorithm based on motion information such as the speed of nodes is proposed to eliminate the error of round-trip-time correction. Meanwhile, a simplified version of our algorithm is put forward to cope with some resource-constrained scenes. Our algorithm can perform well in most situations and effectively improve the clock synchronization accuracy with reasonable communication overhead, especially in high-speed scenes. Simulation results confirm the superior accuracy performance achieved by our algorithm.

This paper deals with joint optimization of rate and power for NOMA-based layer-aware multicasting systems. We encode the source information into multiple layers with successive enhancement, and fix the ratios between the rates of any two layers. Superposition coding (SC) and successive interference cancellation (SIC) are applied to approach the capacity of broadcast channels. Based on channel statistics known at the transmitter, we adapt the integral transmission rate and the power allocation in order to maximize the expected user satisfaction defined by a utility function. We solve the problem by splitting it into several typical cases, each of which eliminates a different number of upper layers. We show the strong duality of each case and propose a two-dimensional bisection search algorithm to solve the dual problem. Simulation and discussion are under both i.i.d. and non- i.i.d. scenarios.

The integration of radar and communication has attracted general interest with its advantage of equipment miniaturizing and high efficiency of spectrum, especially in intelligent transportation systems because of the need for transmitting and detecting simultaneously and the lack of room for various devices. Among various integration schemes, the integrated waveform which realizes transmitting and detection at the same time is a real integration with high efficiency and no interference. In this paper, we proposed a modified three-section integrated waveform based on linear frequency modulation and continuous phase modulation (LFM-CPM). Short Time Fourier Transform (STFT) is used for time-frequency analysis and the modification of the mapping codebook of the communication symbols restrains the spectrum of the integrated waveform within the original bandwidth of the radar system. Simulation results show that the modified waveform holds good bit error rate (BER) performance even when there is strong interference beside the original bandwidth of the radar system, while the waveform without modification can hardly complete the transmission with high BER.

The joint radar-communication system is a good way to meet the intelligent transportation systems' need of detecting the cars and barriers around and exchanging information from each other at the same time. Among various schemes, the joint system with integrated waveform attracts general interest because the interference between the radar and communication subsystems will be fundamentally avoided. For all kinds of integrated waveforms, the spectrum must be limited within B0, the original working band of the radar, in order to avoid the performance loss brought by the attenuation of the power amplifier (PA) and the interference from other devices out of band, which is inevitable in actual devices and environment. In this paper, the time-frequency characteristics of an integrated waveform based on Linear Frequency Modulation (LFM) and Continuous Phase Modulation (CPM) is studied in detail with the Short Time Fourier Transform (STFT). Based on the theoretical analysis, a modified three-section waveform with a limit of the mapping codebook of communication symbols is proposed. Simulation results show that the bandwidth of the modified waveform is limited within B0and the bit error rate (BER) performance with a band-limited PA and out-band interference is almost the same as the BER with ideal PA and no interference.

Single frequency network (SFN) is a promising technology for broadcasting systems with the advantages of better coverage and higher spectral efficiency. However, transmitting local services with unequal contents in SFN remains to be a problem. Bit division multiplexing (BDM) enables local service insertion (LSI) by dividing the channel resources into two sub-channels at bit level, which can approach the theoretical bound of total capacity than traditional time division multiplexing (TDM) method. With BDM, the transmission of global services enjoys all SFN advantages, at the same time each local content uses the same frequency layer. The coverage ratio of global service area (GSA) and local service areas (LSAs) are limited due to interference and reception thresholds. This paper deals with the option of BDM strategy and the adaption of transmitter parameters to optimize the overall coverage performance. A metaheuristic optimization approach using genetic algorithm (GA) is proposed. The simulation and discussion are based on a realistic scenario.

Optical wireless communication (OWC) has been a rapidly growing research area in recent years. Applying multiple-input multiple-output (MIMO), particularly large-scale MIMO, into OWC is very promising to substantially increase spectrum efficiency. However, one challenging problem to realize such an attractive goal is the practical signal detection algorithm for optical MIMO systems, whereby the linear signal detection algorithm like minimum mean square error (MMSE) can achieve satisfying performance but involves complicated matrix inversion of large size. In this paper, we first prove a special property that the filtering matrix of the linear MMSE algorithm is symmetric positive definite for indoor optical MIMO systems. Based on this property, a low-complexity signal detection algorithm based on the successive overrelaxation (SOR) method is proposed to reduce the overall complexity by one order of magnitude with a negligible performance loss. The performance guarantee of the proposed SOR-based algorithm is analyzed from the following three aspects. First, we prove that the SOR-based algorithm is convergent for indoor large-scale optical MIMO systems. Second, we prove that the SOR-based algorithm with the optimal relaxation parameter can achieve a faster convergence rate than the recently proposed Neumann-based algorithm. Finally, a simple quantified relaxation parameter, which is independent of the receiver location and signal-to-noise ratio, is proposed to guarantee the performance of the SOR-based algorithm in practice. Simulation results verify that the proposed SOR-based algorithm can achieve the exact performance of the classical MMSE algorithm with a small number of iterations.

Free-space optical (FSO) communications can achieve high capacity with huge unlicensed optical spectrum and low operational costs. The corresponding performance analysis of FSO systems over turbulence channels is very limited, particularly when using multiple apertures at both transmitter and receiver sides. This paper aims to provide the ergodic capacity characterization of multiple-input-multiple-output (MIMO) FSO systems over atmospheric turbulence-induced fading channels. The fluctuations of the irradiance of optical channels distorted by atmospheric conditions is usually described by a gamma-gamma (rr) distribution, and the distribution of the sum of rr random variables (RVs) is required to model the MIMO optical links. We use an α - μ distribution to efficiently approximate the probability density function (pdf) of the sum of independent and identical distributed ΓΓ RVs through moment-based estimators. Furthermore, the pdf of the sum of independent, but not necessarily identically distributed ΓΓ RVs can be efficiently approximated by a finite weighted sum of pdfs of ΓΓ distributions. Based on these reliable approximations, novel and precise analytical expressions for the ergodic capacity of MIMO FSO systems are derived. Additionally, we deduce the asymptotic simple expressions in high signal-to-noise ratio regimes, which provide useful insights into the impact of the system parameters on the ergodic capacity. Finally, our proposed results are validated via Monte Carlo simulations.

In this paper, we study the optimal broadcast radius in cellular network from the perspective of energy efficiency. Firstly, we consider the scenario where the base stations have already been deployed. The relationship between the power-saving gain and the possible energy efficient broadcast radius is derived. Based on it, we investigate the optimal number of tiers of cells in the broadcast range. Next, we turn to the scenario with the base stations to be deployed. The power consumption per effective coverage area is defined to measure the energy efficiency of different broadcast radius, based on which we analyze the optimal broadcast radius under different channel conditions. Simulation results confirm that the optimal energy efficient broadcast radius is positively correlated with the static power of the broadcast channel, negatively correlated with the minimal required broadcast service rate in the two scenarios, and negatively correlated with the original cell radius in the first scenario.

Minimum mean square error (MMSE) signal detection is near-optimal for uplink multi-user large-scale MIMO systems with hundreds of antennas at the base station, but involves matrix inversion with high complexity. In this paper, we first prove that the filtering matrix of the MMSE algorithm in large-scale MIMO is symmetric positive definite, based on which we propose a low-complexity signal detection algorithm by exploiting the Richardson method to avoid the complicated matrix inversion. The proof of the convergence of the proposed scheme is also provided. We then propose a zone-based initial solution by simply checking the values of the received signals, which can accelerate the convergence rate of the Richardson method for high-order modulations to reduce the complexity further. The analysis shows that the complexity can be reduced from O(K3) to O(K2) by the proposed signal detection algorithm, where K is the number of users. Simulation results indicate that the proposed algorithm outperforms the recently proposed Neumann series approximation algorithm and achieves the near-optimal performance of the classical MMSE algorithm.

In time-domain synchronous OFDM (TDS-OFDM) system for digital television terrestrial multimedia broadcasting (DTMB) standard, the baseband OFDM signal is upsampled and shaping filtered by square root raised cosine (SRRC) filter before digital-to-analog converter (DAC). Much of the work in the area of timing synchronization for TDS-OFDM focuses on frame synchronization and sampling clock frequency offset recovery, which does not consider the sampling clock phase offset due to the upsampling and SRRC filter. This paper evaluates the bit-error-rate (BER) effect of sampling clock phase offset in TDS-OFDM system. First, we provide the BER for M-order quadrature amplitude modulation (M-QAM) in uncoded TDS-OFDM system. Second, under the condition of the optimal BER criterion and additive white Gaussian noise (AWGN) channel, we propose a near optimal sampling phase estimation criterion based on frequency-domain response. Simulations demonstrate that the proposed criterion also has good performance in actual TDS-OFDM system with channel coding over multipath channels, and it is superior to the conventional symbol timing recovery methods for TDS-OFDM system.

In this paper, we focus on designing energy-efficient opportunistic multicast scheduling method and user sleeping mechanism for scalable video transmission in a wireless network. The goal is to minimize the total energy consumption for receiving video data with bandwidth constraint and users' minimum QoS requirements. To utilize opportunistic multicast scheduling, unequal erasure protection (UXP) scheme is used for scalable video at the application layer. Considering the encoding characteristics and unequal protection scheme of scalable video, the UXP frame-level QoS is defined. And a low-complexity scheduling algorithm is proposed by transforming frame-level QoS requirement into slot-level QoS requirement at each time slot dynamically. Simulation results shows that our proposed algorithm can achieve better tradeoff between users' energy consumption and QoS requirements than conventional multicast scheduling schemes. Besides, multicast users' energy efficiency can be improved further if larger decoding delay is allowed at the receiver.

In this paper, we analyze the conventional unequal erasure protection (UXP) scheme for scalable video transmission, and propose a dynamic hybrid UXP/ARQ transmission framework to improve the performance of the conventional UXP method for bandwidth-constrained scalable video transmission. This framework applies automatic retransmission request (ARQ) to the conventional UXP scheme for scalable video transmission, and dynamically adjusts the transmission time budget of each group of picture (GOP) according to the feedback about the transmission results of the current and previous GOPs from the receiver. Besides, target video quality is introduced and optimized to adapt to the channel condition in pursuit of more efficient dynamic time allocation. Simulation results show that compared with the conventional UXP scheme, the average peak signal to noise ratio (PSNR) of the reconstructed video can be improved significantly in a wide range of packet loss rate.

Compared with the global positioning system (GPS), the digital television (DTV) broadcasting signal is a promising candidate for position location due to low implementation cost and strong signal reception. Without changing the current infrastructure of the Chinese DTV broadcasting network, this paper proposes a novel positioning scheme using the multi-carrier pseudo-noise (PN-MC) training sequence in the guard interval of the time domain synchronous OFDM (TDS-OFDM) signal frame. Different from the existing positioning methods based on timing synchronization or super resolution algorithms, the joint time-frequency estimation utilizing the properties of the received PN-MC sequence both in the time and frequency domain with respect to transmission delay, results in the accurate time of arrival (TOA) estimation. Performance of the proposed scheme is evaluated by Monte Carlo simulations in comparison with other the-state-of-art methods. The positioning accuracy of less than 0.1 m when the signal-to-noise ratio (SNR) is greater than 15 dB is achieved, under both the additive white Gaussian noise (AWGN) and the simulated multi-path channels.

H.264/AVC scalable video coding (SVC) is an upto-date video compression standard. This paper deals with the issue of transmitting H.264 scalable video bitstreams over wireless fading channels. The contribution is twofold: Firstly, to exploit the importance of prioritized video packets in different temporal layer, quality layer and group of pictures (GOP), a simple and accurate performance metric, namely, layer-GOP-weighted expected zone of error propagation (LGW-EZEP) model is proposed. Secondly, a joint power control and forward error correction (FEC) unequal error protection (UEP) scheme is proposed to transmit the video streams over orthogonal frequency division multiplexing (OFDM) systems efficiently and robustly. Meanwhile, a new iterative algorithm is given to solve the joint optimization problem. Compared to other independent power control or FEC UEP schemes, the combined protecting scheme demonstrates stronger robustness and flexibility via various fading channels.

In this paper, we study the impact of time-selective fading on quasi-orthogonal space-time (ST) coded orthogonal frequency-division multiplexing (OFDM) systems over frequency-selective Rayleigh fading channels. OFDM is robust against frequency-selective fading, but it is more vulnerable to time-selective fading than single-carrier systems. In ST-OFDM, channel time variations cause not only intercarrier interference among different subcarriers in one OFDM symbol, but also intertransmit-antenna interference. We quantify the impact of time-selective fading on the performance of quasi-orthogonal ST-OFDM systems by deriving, via an analytical approach, the expressions of carrier-to-interference and signal-to-interference-plus-noise ratios. We observe that system error performance is insensitive to changes in vehicle speeds and the channel power-delay profile, but very sensitive to changes in the number of subcarriers. We also evaluate the performance of five different detection schemes in the presence of time-selective fading. We show that although there exist differences in their relative performances, all these detection schemes suffer from an irreducible error floor.

Orthogonal frequency division multiplexing (OFDM) is robust against frequency selective fading, but it is very vulnerable to time selective fading. In quasi-orthogonal space-time coded OFDM (ST-OFDM) systems, channel variations cause not only inter-carrier interference among different subcarriers in one OFDM block, but also inter-transmit-antenna interference (ITAI). When applied in fast fading channels, common ST-ODFM receivers usually suffer from an irreducible error floor. In this letter, we apply frequency-domain correlative coding combined with a modified decision-feedback detection scheme to effectively suppress the error floor of quasi-orthogonal ST-OFDM over fast fading channels. The effectiveness of the proposed scheme in mitigating the effects of channel time selectivity is demonstrated through comparison with existing schemes such as zero-forcing, two-stage zero-forcing, and sequential decision feedback estimation