The noncoherent single-input-multiple-output (SIMO) system experiences severe cross-product mutual interference with a limited number of receive antennas, severely limiting the number of simultaneous users that can be served in the uplink. In Rician channel, a multiuser energy difference detection (EDD) scheme is introduced for dual-frequency complementary amplitude signals. It eliminates cross-product interference, significantly reducing the number of antennas required by the base station (BS), while extending the constellation space for energy detection (ED). Based on this extended constellation space and channel gain information, two optimized multiuser constellations are obtained by maximizing the minimum joint constellation distance and directly equalizing the receive constellation space. Additionally, the impacts of user mobility are analyzed, and a simple strategy is designed to maintain performance by updating the moving user’s path gain. Simulation results show that the proposed scheme can handle more simultaneous users with the same scale antennas, and it also exhibits strong robustness to user mobility at the same time.

Compared with terrestrial network, the air-ground integrated network consisting of unmanned aerial vehicles (UAVs) and high altitude platforms (HAPs) offers the advantages of large coverage, high capacity, and seamless connection. Therefore, the air-ground integrated network can provide effective communication services for the Internet of remote things (IoRT). In order to reduce the end-to-end (e2e) packet delay and avoid network congestion of the two-hop network, we investigate a joint packet scheduling, resource allocation, and UAV trajectory design problem, with the objective of minimizing the average packet queue delay from HAP to IoRT devices in the air-ground integrated network. This problem is non-convex and difficult to solve by the traditional methods. In order to solve this problem, we reformulate it into a Markov decision process (MDP) firstly. And then, considering there are continuous and discrete hybrid action spaces in the MDP, we separate the primal action spaces into two sub-action spaces, and utilize the basic idea of multi-agent deep deterministic policy gradient (MADDPG) and multi-agent double deep Q network (MADDQN) methods to solve them, respectively. After that, in order to improve the stability, convergence rate and learning efficiency, we introduce the basic idea of adaptive prioritized experience replay, and propose a hybrid MADDPG-adaptive prioritized experience replay (MADDPG-APER) algorithm. Simulation results show that the proposed algorithm can reduce the average packet queue delay compared with other benchmark algorithms.

Abstract Carrier aggregation can not only increase communication bandwidth, but also improve spectrum efficiency and communication security. Considering the non‐contiguous multi‐subspectrum aggregation for the spectrum division transmission of arbitrary signal, the paper analyzes the performance impact on the demodulation of aggregated signal in the presence of subspectral amplitude and phase errors in receiver. The theoretical bit‐error rates (BER) of quaternary phase‐shift keying and M ‐ary phase‐shift keying are derived to clarify the subspectrum synchronization accuracy requirements in non‐contiguous carrier aggregation. In addition, two adaptive equalizers requiring no pilot overhead are introduced to correct the distortion of aggregated signal caused by the subspectral errors. Both algorithms need no estimation of synchronization error but also have the tracking capability of phase error even with subspectral carrier error. Simulation results show the reliability of the theoretical BER performance and the excellent performance of the equalization algorithms.

Under the condition of limited number of antennas in current noncoherent single-input-multiple-output (SIMO), the key problems of serious mutual interference and small number of supported users are still difficult to overcome. In this paper, we proposed a multi-user massive SIMO based on energy difference detection (EDD) in Rician channels. The proposed method only needs to simply estimate the line-of-sight (LOS) amplitude gain of users. The cross-product interference caused by energy detection is eliminated by designing complementary amplitude constellations and performing energy difference detection at the base station (BS). It reduces the number of antennas required by the BS to distinguish data streams from different users. In addition, we also analyze the impact on the system performance when users move, and adopt the low-complexity approach of re-estimating the moving user’s coefficient to maintain a good performance. Simulation results show that the proposed method can use the LOS component of the Rician channels to support more concurrent users, and obtain a better performance than existing methods.