Physical Layer Innovations for 6G Space-Air-Ground Integrated Networks

Cognitive radio (CR) acts as a significant player in enhancing the spectral efficiency (SE) of wireless telecommunications; simultaneously, the intelligent reflecting surface (IRS) technique is a valid technique for increasing the confidentiality properties of wireless telecommunications systems through the modulation of the amplitude and phase shift of the channel. Therefore, we take into consideration an IRS-assisted multiple-input single-output (MISO) CR system to raise the confidentiality rate, which is composed of a primary network with a primary receiver (PR) and an eavesdropping link, as well as a secondary network with a secondary receiver (SR) and SR transmitter (SR-TX). In particular, we minimize the SR’s transmit power under the interference temperature (IT) and confidentiality capacity constraints via the joint optimization of the beamforming vector and artificial noise (AN) constraint matrix at SR-TX together with the phase shift matrix of IRS. Numerical outcomes indicate that various transmit antenna values and the IRS element numbers at SR-TX can greatly reduce transmit power while assuring secure communication. Full article

Intelligent transport systems (ITSs) rely on wireless communications that provide many services to ground and aerial vehicles. We believe that vehicular communication protocols can evolve the train communication systems into the next generation. However, we found that channel models in train track environments at the 5.9 GHz frequency band are scarcer than in vehicular environments. Therefore, we conduct channel measurements at the 5.86–5.91 GHz ITS band at various railroad crossings in the United States. This allows us to extract the channel parameters and evaluate the propagation channel characteristics. The evaluations show a certain similarity between the train track channel characteristics and the vehicular communications channel characteristics. The railroad channel with an omnidirectional antenna is similar to a suburban environment in the vehicular channel, and with a bidirectional antenna, it is similar to a highway LoS environment in the vehicular channel. However, more importantly, the population of the surrounding buildings and the size of the LoS window can highly affect the RF propagation characteristics. Full article

Unmanned-aerial-vehicle (UAV)-aided data collection for Internet of Things applications has attracted increasing attention. This paper investigates motion planning for UAV collecting low-power ground sensor node (SN) data in a dynamic jamming environment. We targeted minimizing the flight energy consumption via optimization of the UAV trajectory while considering the indispensable constraints which cover the collection data demodulation threshold, obstacle avoidance, data collection volume, and motion principle. Firstly, we formulate the UAV-aided data collection problem as an energy consumption minimization problem. To solve this nonconvex optimization problem, we rewrite the original problem by introducing relaxation variables and constructing equivalence constraints to obtain a new relaxation convex problem, which can be solved iteratively using the successive convex approximation (SCA) method. However, SCA is susceptible to initial values, especially in dynamic environments where fixed initial values may lead to a wide range of results, making it difficult to obtain a truly optimal solution to the optimization problem. To solve the initial value problem in dynamic environments, we further propose a communication-flight-corridor(CFC)-based initial path generation method to improve the reliability and convergence speed of the SCA method by constructing reliable communication regions and resilient secure paths in real time. Finally, simulation results validate the performance of the proposed algorithm compared to the benchmark algorithms under different parameter configurations. Full article

Reinforcement learning (RL) has been successfully applied to underwater routing protocols due to its powerful ability of distributed decision making. However, the traditional RL has slow convergence speed and low learning efficiency in underwater. Meanwhile, too many studies focus on using RL to find low hop paths rather than short distance paths in underwater routing, while the long distance of ocean communication is the significant reason for the packets collision and energy loss in underwater. Based on the above problems, this paper proposes the PDDQN-HHVBF (Empirical Priority DDQN to Improve Hop-by-Hop Vector-Based Forwarding) protocol for M-UWSNs (Mobile source node Underwater Wireless Sensor Networks), in which AUV (Autonomous Underwater Vehicle) is used as source node to collect data and transmit data hop-by-hop to Sink node through underwater nodes. The proposed protocol is adopt to find the optimal relay nodes in pipeline referred HHVBF protocol by requesting the max Q value according to three states of the residual energy of nodes, the number of candidate relay nodes and the geographical location information of all candidate relay nodes in time. This because PDDQN-HHVBF avoids the strong correlation between data samples, and its playback samples will not be too concentrated or lead to over fitting. It can converge rapidly in underwater environment. In addition, the requesting Q value mechanism related to the geographical location information can find the optimal relay node with short distance propagation in large-scale networks, which will reduce the number of packets collision, and then saving energy and improving network lifetime. In addtion, the in-time requesting for Q value can cope with the nodes drift affected by ocean current movement. In addition, the Q value related to the residual energy of nodes and the number of candidate relay nodes will effectively load balancing nodes, prolong network lifetime and avoid routing holes. Finally, the “Store-Carry-Forward” mechanism proposed for AUV, this mechanism store and carry packets when facing routing holes until find the optimal relay node for forwarding, which will improve PDR and save energy of AUV significantly. The simulation results show that, the proposed PDDQN-HHVBF protocol converges about 30% faster than DQELR. Although its delay is higher than DQELR and ROEVA for requesting Q value. It outperforms VBF, HHVBF, DQELR, and ROEVA in terms of energy efficency, PDR, and lifetime, which are analyzed by varying speed of nodes from 0 m/s to 3 m/s with 1000 nodes and varying number of nodes from 500 to 3000 with speed in 1 m/s. Full article

In this paper, we propose efficient computational solutions for estimating the statistical properties of wide-sense stationary un-correlative scattering (WSSUS) and non-WSSUS multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) channel models. Specifically, in the WSSUS channel models, we first estimate the angle of departure (AoD) for the non-line of sight (NLoS) propagation components. In this manner, the complex channel impulse response (CIR), which are widely used in the existing literature to characterize the wireless channel physical properties, can be estimated on the basis of the estimated AoD and defined model parameters. Conversely, in the non-WSSUS channel models, by estimating the AoD in the initial stage, the real-time complex CIR of the V2V channel model can be estimated on the basis of the estimated AoD and the moving time/velocities/directions of the mobile transmitter (MT) and mobile receiver (MR). In the estimation process of the aforementioned cases, we introduce different solutions to convert the CIRs from the complex domain to the real-value domain, thereby optimizing the computational efficiency for investigating channel characteristics as compared to existing methods. Numerical results of the WSSUS and non-WSSUS MIMO V2V channel characteristics, such as the spatial-temporal (ST) cross-correlation functions (CCFs) and auto-correlation functions (ACFs), are estimated on the basis of the estimated complex CIRs. These results are in agreements with theoretical ones, indicating that the proposed algorithms are practical for estimating the WSSUS and non-WSSUS MIMO V2V channel characteristics. Full article