The era of artificial intelligence and big data has witnessed an explosive growth in computational demands. The von Neumann architecture faces constraints from the “memory wall” and “power wall” due to its separation of storage and computation. Compute‐in‐memory (CIM) technology has emerged as a key pathway to overcome the von Neumann bottleneck. As a novel class of semiconductor devices capable of both storage and computation, memristors offer advantages such as simple structure, low‐power consumption, and great potential for high‐density integration, showing great promise for CIM architectures. This article provides a systematic review of the latest research progress on memristors in terms of their operating mechanisms, array integration, and applications. It mainly focuses on the working principles, performance characteristics, and optimization strategies of four types of memristors based on the conductive filaments, phase‐change, magnetic tunnel junction, and ferroelectric tunnel junction mechanisms. Key performance parameters of various memristive devices are compared. In addition, the paper introduces multiple integrated solutions for overcoming sneak‐path current interference, presents typical application cases of memristors, and provides an outlook on future development, serving as a reference for further research on memristors.

Travel data is vital for understanding individual travel behaviors and estimating travel demand. Compared with traditional travel surveys in which respondents were asked to recall their trips, smartphones can record GPS trajectories actively at a high level of accuracy in both space and time. However, how to identify trips and detect travel modes from raw GPS data in an efficient way is still challenging. To address these issues, we firstly target high-accuracy data collection through developing a smartphone-based person travel survey system which comprises of three components, i.e., data collector, data processor, and data validator. The data collector is a smartphone app for collecting GPS trajectories; the data processor is a server embedded with rule-based algorithms to extract travel-activity information; and the data validator is a webpage to present the self-extracted travel information for respondents’ validation. Secondly, we propose a hybrid random forest and merging algorithm to detect multiple travel modes in complex trips. The algorithm reaches an accuracy of 100% for simple trips and 95.7% for multimodal trips. These results indicate that the proposed hybrid random forest and merging algorithm can help identify travel modes of complex trips more accurately and efficiently.

Multi-Connectivity (MC) is a key technology in the deployment of the upcoming Fifth Generation (5G). MC means that one user can connect to a Master Evolved NodeB (MeNB) as well as several Secondary Next Generation NodeBs (SgNBs) simultaneously. According to MC, MeNB will forward a portion of traffic to SgNBs through non-ideal backhaul, while the remaining traffic will be served by itself. An efficient traffic splitting scheme has great impacts on the performance of MC. In this paper, we propose a goodput-aware traffic splitting scheme based on queuing theory and goodput model. Taking the nonideal backhaul delay as well as the buffer status of MeNB and SgNBs into consideration, the proposed traffic splitting scheme can adaptively optimize the system goodput. Simulation results verify that the proposed goodput-aware traffic splitting scheme effectively contributes to the goodput increment.

The fifth generation (5G) wireless network faces unprecedented massive concurrent random access requests in uplink (UL) contention-based (CB) transmission. In this paper, a non-orthogonal coded access (NOCA) UL transmission in combination with parallel interference cancellation (PIC) based reception scheme at base station is investigated. Non-orthonormal code generated by Zadoff-Chu (ZC) sequences is used to spread the data bits over orthogonal frequency division multiple (OFDM) symbols. It is shown through both link level and system level simulations that in dense urban scenario NOCA-PIC scheme is capable of working in highly overloaded system conditions. It can support more than 4 times concurrent random access number compared with OFDM based CB transmission.

The contention-based (CB) transmission is a promising solution for small data packets transmission in 5G uplink. In this paper, a Non-Orthogonal Coded Access (NOCA) scheme, called ZC-NOCA, is proposed for CB transmission in 5G uplink. For ZC-NOCA, the codes generated by Zadoff-Chu (ZC) sequences is used to spread the data bit over the Orthogonal Frequency Division Multiple (OFDM) symbols. Different with LTE, where ZC sequences keep inter-cell orthogonal, ZC-NOCA use both non-orthogonal and orthogonal sequences for spreading. A CB transmission channel design with ZC-NOCA for 5G uplink is presented, to combine the advantages of both orthogonal and non-orthogonal schemes. The link level performance of ZC-NOCA is investigated by using two types of multi user detection (MUD) receiver considering the user detection performed by preamble or directly by the spreading codes. The study show ZC-NOCA allow a large number of user overloading and enable massive connections employed with CB transmission. Compare to orthogonal code access scheme, with larger code book length ZC-NOCA enables to support more than 10x user connections with acceptable link performance loss in CB transmission.

In this paper, we focus on a new small cell discovery signal which improves the detection probability in ultra-dense small cell scenario. Due to the severe inter-cell interference, the detection performance of primary synchronization signal (PSS) and secondary synchronization signal (SSS) is deteriorated in future ultra-dense small cell scenario in the 3rd Generation Partnership Project (3GPP) long term evolution (LTE) system. Thus the current supported 504 cell IDs may not be sufficient. To mitigate the impact of such inter-cell interference problems and improve the cell search performance with increasing number of detect target cells, we propose a novel defined auxiliary secondary synchronization signal (A-SSS) in cell search procedure. Our simulation results show that the detection probability of cell search can be improved effectively with the proposed method.

Coordinated multi-point transmission/reception (CoMP) has been identified as an important way of mitigating interference and improving spectral efficiency for cell edge users in LTE-A system. However, current CoMP studies mainly focus on joint transmission (JT), dynamic point selection (DPS) and coordinated scheduling/beamforming (CS/CB) which all fall into closed-loop category. When considering medium or high mobility users, closed-loop CoMP seems less effective, while open-loop CoMP is more preferred, which is similar to that observed between closed-loop and open-loop single user multiple-input multiple-output (SU-MIMO). In this paper, we propose open-loop CoMP transmission frameworks for both spatial multiplexing and transmit diversity. We design our open-loop CoMP schemes by reusing long term evolution (LTE) open-loop SU-MIMO structures as much as possible to alleviate standardization efforts, and especially consider support for demodulation reference signals (DM-RS) which will be prevalent in future LTE-Advanced systems. Simulation results verify the effectiveness of our proposed open-loop CoMP schemes.

A new adaptive irregular modulation technique is proposed for Turbo iterative detected multi-antenna system with different bit mapping schemes or (and) modulation schemes used in different transmit antennas. The modulation scheme and the bit mapping scheme can be adaptively chosen according to the time varying channel quality to improve the channel throughput. When combining the proposed approach and the irregular modulation scheme, it can provide more flexible adaptation to the current channel quality. Simulation results show that using this adaptive technique, the system can converge earlier without changing the system throughput; meanwhile, system using this adaptive method can have higher system throughput compared with conventional adaptive method.