In MIMO systems, hybrid digital and analog precoding structures are gaining attention for reducing power consumption and costs compared to fully digital precoding. However, deployment expenses and circuit power consumption still pose challenges. Nonideal hardware in practical applications further impacts energy efficiency (EE), making research into high-energy-efficiency MIMO structures under such conditions essential. To tackle this issue, an exceedingly effective hybrid precoding strategy is developed, incorporating the implications of nonideal hardware characteristics. Initially, the research models the aforementioned hardware characteristics, formulates the signal model for the hybrid-structured MIMO communication system, and discerns the nonconvex problem relative to energy efficiency optimization. Subsequently, the optimization problem is effectively resolved by choosing analog radio frequency (RF) precoding and digital baseband precoding designs, including the precoding design for array gain. Furthermore, fractional programming is utilized to achieve digital precoding. An iterative optimization method is utilized to solve this problem. Finally, the mixed precoding scheme is formulated to showcase the system’s energy efficiency performance through simulation and explore the impact of imperfect hardware on the system. Additionally, to further diminish design complexity, the implementation of various channels is analyzed to propose a low-complexity method via the approximation of the equivalent channel matrix. Simulation results show that the performance of this method achieves performance comparable to existing hybrid precoding methods, when the number of antennas is sufficiently large.

A millimeter wave (mmWave) line-of-sight (LOS) multi-input-multioutput (MIMO) system is studied, where spatial multiplexing is achieved through LOS transmissions in near-field areas. A comprehensive analysis of the achievable rate in mmWave LOS MIMO system with respect to the rotation of uniform linear arrays (ULAs) is provided for both full-rank orthogonal and rank-deficient LOS MIMO channels. 1) For full-rank orthogonal scenarios, the necessary and sufficient condition for the LOS MIMO system to have the maximum achievable rate is established. 2) For rank-deficient scenarios, a closed-form expression for the Degrees of Freedom (DoF) of mmWave LOS MIMO channels is derived. Subsequently, the alternating phase approximation-based (APA-based) hybrid precoding algorithm is proposed, where the number of radio frequency (RF) chains is determined by the DoF of mmWave LOS MIMO channels and the initial phase of iterative optimizations is determined according to the optimal digital precoder. Our numerical results confirm the effectiveness of our analysis and proposed algorithm. It is also unveiled that 1) the DoF can be maximized through a specific angle design and 2) compared to existing hybrid precoding algorithms, our proposed APA-based hybrid precoding algorithm exhibits superior robustness against the angular rotation of ULAs.

In this study, a joint blind frame synchronization and decoding method is proposed based on the normalized syndrome satisfaction probability (NSSP) provided by the soft Low-Density Parity-Check (LDPC) codes decoder. To reduce complexity, a stopping criterion is introduced into the iterative process through the convergence of NSSP evolution patterns. In addition to achieving an excellent synchronization performance, this method also eliminates the redundancy caused by the pilot sequence. Furthermore, it is compared with the optimal pilot-based and other code-aided frame synchronization algorithms. According to analytical and simulation results, the proposed technique outperforms other advanced code-aided frame synchronization solutions in synchronization, which makes it applicable to achieve comparable performance to the pilot-based methods in specific coding gains. Due to the introduction of a novel stopping criterion, the average number of joint detection & decoding is reduced by up to 90%. Analog probability processing technology integrates sub-threshold region circuits with probability domain-based iterative message-passing algorithms inspired by high energy efficiency and low complexity. Hence, hardware implementation is presented based on the analog LDPC decoder chip as fabricated in a 0.35-μm CMOS technology for our proposed algorithms. The experimental results demonstrate the effectiveness of the proposed method and the realization loss is within 0.2 dB compared with the theoretical circuit simulation results.

The dependable transmission of data and the efficacy of wireless communication depend critically on the detection and classification of interference. Traditional classification algorithms may not yield the requisite precision in identifying and categorizing diverse types of interference, whereas deep learning (DL) algorithms necessitate high-quality data and training samples, which prove unfeasible in real-time communication scenarios. In addressing these challenges, we present a novel approach that utilizes the denoising diffusion probabilistic model (DDPM) for offline processing of collected signals before feature extraction and subsequently sending the signals into a predefined classifier. Our experimental analyses show that our approach delivers up to 91% accuracy without any prior information, outperforming both generative adversarial network (GAN)-based and other traditional DL algorithms, even with limited signal samples of only 5. More significantly, our approach underscores the feasibility of employing generative models in signal processing and achieves state-of-the-art performance on high-precision recognition in real-world communication scenarios.

We propose a cluster-based multi-carrier beam division multiple access (MC-BDMA) scheme to enable massive device terahertz (THz) communications with the dynamic-subarray hybrid beamforming (HBF) architecture. This scheme is motivated by a limitation of conventional HBF architectures, i.e., the number of users cannot exceed the number of radio frequency (RF) chains. By exploiting the unique properties of THz channels, such as high distance-and-frequency dependence, high sparsity, and small angular spread, we propose multiple users in the same cluster to be supported by a single RF chain with distance-aware multi-carrier modulation. Moreover, we propose different clusters to be divided by BDMA that is accomplished through HBF design. In our proposed scheme, we first design a novel antenna selection and subarray partition algorithm for the dynamic-subarray HBF architecture to compensate for performance loss caused by diverse channels among users. We then design an algorithm for multi-carrier HBF which maximizes the achievable throughput and eliminates the inter-beam interference. Numerical results show that our proposed cluster-based MC-BDMA scheme with the dynamic-subarray HBF architecture provides an almost 100% spectral efficiency gain and a 60% energy efficiency gain over the conventional non-cluster HBF scheme in massive device communications.

As the symbol rate gradually increases, inter-symbol interference becomes more serious. High-performance and low-resource equalization technology has become one of the research hotspots in the signal processing area. In this paper, for channel with constant characteristics, a digital-analog hybrid equalizer of broadband signals based on equivalent time sampling is proposed. The equivalent time sampling technology can reconstruct signals at a sampling rate much lower than the Nyquist sampling rate, thus, it can greatly alleviate the pressure on the ADC and reduce the processor's resource consumption. In addition, the dual-mode blind equalization algorithm can achieve fast convergence and accurately compensate for errors caused by non-ideal channel. Moreover, the numerical results show that the performance of the dual-mode multi-modulus algorithm and decision-directed algorithm (MMA-DD) is better than the multi-modulus algorithm (MMA) which can further reduce the residual error to accurately track the channel characteristics.