Dehuan Wan

With the development of 6G wireless networks, nonfixed monitoring methods utilizing drone networks as monitoring carriers have been receiving increasing attention. However, due to significant environmental interference affecting the hovering of drones in the air, the video signals often contain substantial random interference, which impacts the performance of current multiobject and multicamera tracking (MOMCT) algorithms. To address this issue, this article proposes a digital-twin-driven multivehicle multidrone monitoring system, in which a simulation scenario consistent with the actual environment is created. Furthermore, a large amount of vehicle monitoring video data from multiple drone perspectives with random interference is generated, thus compensating for the shortage of multicamera vehicle monitoring data, especially data affected by random interference. In addition, an online tracking framework for MOMCT based on the digital-twin system is set up, forming a pipeline that fully utilizes the simulated data generated by the digital-twin system for training and testing. Using this pipeline, we find that a feature detection algorithm combining AttentionNet-CBAM and ResNext101-IBN-A can effectively enhance the ability to identify target features, thereby achieving better multivehicle tracking results. Experimental results on the CityFlow dataset verify that the proposed method has improved the identification $F1$ -score (IDF1) by 1.52% and identification recall (IDR) by 3.58% in comparison with the state-of-the-art online MOMCT methods.

The integration of probability-based hierarchical clustering routing with sleep scheduling is essential for topology control in achieving energy optimization within energy-constrained wireless sensor networks (WSNs). However, it encounters numerous challenges, such as the selection of low energy nodes as cluster heads (CHs), non-uniform distribution of CHs, large overlapping areas between nodes, and unreasonable setting of sleep probability. To enhance energy efficiency and reduce redundancy, we propose a probability-aware dynamic topology control with sleep scheduling (PDTC), which includes energy and distance weighted dynamic clustering (EDDC) routing and dynamic probability sleep scheduling (DPSS) scheme. EDDC is employed to construct a hierarchical network topology, whereas DPSS is designed to alleviate network load. EDDC prioritizes the node with sizeable residual energy and close to the sink as the CH to equalize energy expenditure. It combines control parameters that encompass residual energy, distance to the sink, and the optimal number of CHs, thereby eliminating the randomness in the selection of CHs. Furthermore, DPSS adopts a recursive method to derive the general expression for the number of active member nodes within a cluster at the beginning of each time slot. It then models the sleep decision as a Bernoulli process to dynamically set the sleep probability for each cluster. This approach probabilistically activates a small number of active member nodes within the cluster to provide intra-cluster communication. The simulation results indicate that our PDTC outperforms existing protocols in terms of network lifetime, the number of alive nodes, and packets received by the sink.

Multiple-mode orthogonal frequency division multiplexing with index modulation (MM-OFDM-IM) is a promising multicarrier transmission technique proposed recently, which focus on exploiting the index domain of the multiple distinguishable modes (constellations) and uses full permutations of the indices of multiple symbol modes to transmit information bits implicitly. Compared to conventional OFDM-IM, a factorial increase of the IM patterns in MM-OFDM-IM prohibits its application in realistic communication systems due to exponentially increased modulation and demodulation complexity when the number of symbol modes is large. In this paper, we propose a novel and efficient MM-OFDM with cascade IM (MM-OFDM-CIM) scheme, which first selects partial symbol modes for multiple mode index modulation (MM-IM) of the first subblock in the cluster and then performs MM-IM based on the rest symbol modes for the second subblock. The proposed CIM method divides the IM process into two steps and achieves considerably low computational complexity in detection. Furthermore, physical layer security can be realized by adjusting the size of subblocks within the cluster due to the flexible CIM designs. Computer simulations show that the proposed MM-OFDM-CIM has potential to achieve near the same bit error rate performance with considerably low computational complexity and achieves excellent secure communication performance between the legitimate users.

In recent years, orthogonal chirp division multiplexing (OCDM) has gained attention as a robust communication waveform due to its strong resistance to both time-domain and frequency-domain interference. However, similar to orthogonal frequency division multiplexing (OFDM), OCDM suffers from a high peak-to-average power ratio (PAPR), resulting in increased hardware costs and reduced energy efficiency of the transmitter’s power amplifiers. In this work, we introduce a novel unitary transform called the Generalized Discrete Fresnel Transform (GDFnT) and propose a new waveform based on this transform, named Generalized Orthogonal Chirp Division Multiplexing (GOCDM). In GOCDM, data symbols from the constellation diagram are independently placed in the Generalized Fresnel (GF) domain. We derive the system’s GF-domain channel matrix under a class of time-frequency doubly selective channels. These channels are characterized by multiple lags and multiple Doppler shifts (MLMDS), making them suitable for application scenarios such as vehicular mobile communication and narrowband underwater acoustic communication. We leverage the sparsity of the GF-domain channel matrix to design an iterative receiver based on the message-passing algorithm. Simulation results demonstrate that GOCDM achieves better PAPR performance than OCDM without compromising bit error rate (BER) performance.

Nonorthogonal multiple access (NOMA) has been recognized as a key enabling techniques for future communication systems since it can take advantage of differences in users’ channel conditions to achieve higher spectral efficiency compared with orthogonal multiple access. However, employing such a capacity-centric framework can result in intragroup co-channel interference for those users whose symbols are intended to be first decoded, potentially causing a decrease in reliability. Therefore, the Alamouti encoding method has been widely used in the multiuser MISO-NOMA broadcast channels to improve reliability. Although the Alamouti-based NOMA paradigm can improve reliability by providing full spatial diversity, it comes at the cost of a significant loss in spectral efficiency compared to the capacity-centric NOMA framework. To overcome these limitations, this article presents a new approach for improving the performance of multiuser MISO-NOMA broadcast channels, in which the diversity-multiplexing tradeoff is leveraged more effectively by providing multiplexing for near users and diversity for far users at the transceiver. The closed-form expressions of ergodic sum-rate and outage probability for the proposed scheme are derived. Simulation results demonstrate that the proposed scheme is capable of performing well in a wide range of scenarios and it surpasses traditional methods in terms of reliability and effectiveness.

Orthogonal frequency division multiplexing with index modulation (OFDM-IM) is a promising multi-carrier technique for next generation wireless communication networks. In this paper, we propose a generalized joint OFDM-IM scheme, which performs joint modulation on multiple sub-subblocks divided from a subblock, to achieve higher spectral efficiency (SE) and lower complexity for both modulation and detection processes. In GJ-OFDM-IM, the subcarrier activation pattern (SAP) of the subblock is composed of the SAPs of all the sub-subblocks within the subblock, which means a large dimensions IM of the subblock is divided into multiple small size IM of the sub-subblocks by taking advantage of the joint modulation. With the aid of joint modulation, the lookup tables for both modulation and demodulation are only related with the size of sub-subblock and not changed with the size of the subblock. At the receiver, the optimal maximum likelihood (ML) detector and a low complexity subblock wise detector are proposed for GJ-OFDM-IM. Then, a tight upper bound on the bit error rate (BER) is derived in closed form to evaluate the system performance of the proposed GJ-OFDM-IM. Simulation and numerical results verify the analysis and show that the proposed GJ-OFDM-IM can greatly reduce the implementation complexity without causing any system BER performance loss compared with classical OFDM-IM.

Crowdsourcing among vehicles, pedestrians, and Base Stations (BSs) in hybrid V2X networks offers a promising approach to enhance subscriber experience by increasing throughput, ensuring driving safety, and supporting autonomous driving. In this letter, we focus on a cooperative hybrid V2X network where vehicles can transmit data directly from base stations through cellular networks or use other vehicles as relays. After recruiting the relay clients to provide cooperative transmission service, the primary client determines how to allocate its traffic among them. Both primary and relay clients aim to maximize their respective reward. This model is formulated as a Stackelberg game. The existence and uniqueness of the Nash Equilibrium (NE) point is achieved under constraints. Simulation results demonstrate that cooperation among vehicles and pedestrians improves the performance of primary clients and encourages relay client participation.

Nonorthogonal multiple access (NOMA) has been widely recognized as a promising spectral efficiency technique for the next generation of wireless communication networks due to its ability to support multiple users in the same orthogonal resource block. In response to the increasing demands for extensive connectivity and high-volume data transmission, a novel index modulation (IM)-aided NOMA scheme has been conceived to improve downlink transmission by capitalizing on the flexibility provided by the constellation rotation design for superposition coding. In the proposed scheme, known as IM aided NOMA with the constellation rotation (IM-NOMA-CR), users are categorized into cell-edge group (far-user accommodated) and cell-center group (near-user accommodated) based on their channel conditions. The rotated constellation-based IM operation is exclusively applied to users in the near-user group, who receive lower power allocations compared to the far-user group, enabling them to transmit additional information while ensuring system reliability. This approach enhances spectral efficiency by activating all subcarriers (orthogonal resource blocks) to transmit information to scheduled users, in contrast to the conventional IM-NOMA scheme. Moreover, extra information can be transmitted through constellation rotation in the superposition coding process, setting it apart from traditional NOMA schemes. Subsequently, the maximum likelihood detector employing successive interference cancellation (ML-SIC) is utilized at the receiving end to decode the intended symbols for all users. Numerical simulations have been carried out to validate the efficacy of the proposed IM-NOMA-CR design, demonstrating a significant enhancement in spectral efficiency and error performance compared to existing NOMA schemes.