Robot swarms, which constitute typical multiuser systems, have played more and more important roles in many areas. In this paper, a directional modulation(DM) scheme for frequency diverse array(FDA) based on the leakage power minimization criterion is proposed, which can be used in a robot swarm system as well as other multiuser scenarios. Based on this scheme, location-dependent secure transmission can be obtained in the multiuser downlink channels under certain circumstances, where independent data streams can be sent to different legitimate users safely. Meanwhile, the difficulty for perfect eavesdropping is significantly increased compared with phased-array-based DM. We also use the block successive upper-bound minimization algorithm to optimize the frequency offsets of the array, and the algorithm can be effectively performed. This scheme utilizes the baseband model of the FDA, which is another contribution of this paper. It solves the problems brought by the time-varying nature of the FDA and reveals the distance-angle correlation of the FDA more fundamentally. Based on that, besides the proposed FDA-DM scheme, a novel multiple access technique, named as link division multiple access, is also preliminarily proposed. It allows the transmitter to distinguish multiple users in the same or proximal locations without the help of time division, frequency division, or code division. At last, numerical results are presented to verify the superiorities of LDMA and the proposed FDA-DM scheme.

Military robot swarm becomes more and more important for contemporary military application. In order to satisfy sophisticated application scenarios, novel communication architecture for military robot swarm has to be conceived. In this paper, we propose a multi-carrier intelligent covert satellite communication (MCICSC) architecture based on electromagnetic environment sensing technology, in where the ability of dynamically adapting the system configuration to the holistic requirements of covertness, performance, and complexity can be considerably improved. Additionally, in order to solve the carrier synchronization problem in very low signal noise ratio (SNR) for each data stream of MCICSC, polar code (PC) is incorporated into the proposed MCICSC system. With the aid of the proposed polar code-aided multi-stream parallel feedback (PAMSPF) carrier synchronization scheme, the MCICSC system is capable of realizing high-precise carrier synchronization even in very low SNR region. Moreover, in order to further decrease the complexity of our MCICSC system, we also propose a polar code-based diversity combining (PBDC) scheme, which is capable of efficiently combing all the data streams without the aid of channel state information (CSI) estimation. Numerical simulations demonstrate that for MCICSC system the performance of the PAMSPF carrier synchronization and PBDC combining schemes can get extremely close to that of an ideally synchronized system. Complexity analysis of the proposed algorithms is given as well.

No abstract

Fast Frequency Hopping/Direct Sequence (FFH/DS) hybrid spread spectrum is an effective technique of the communication network for the robot swarms operating in complex electromagnetic environment. It combines the advantages of both Frequency Hopping Spread Spectrum (FHSS) and Direct Sequence Spread Spectrum (DSSS), and also uses the diversity-combining in time and frequency domain to effectively reject unwanted jamming. Multi-Tone Interference (MTI) is one of the most deleterious jamming waveforms for frequency hopping systems, and consequently a severe threat for FFH/DS systems. In this article, we explore the effect of MTI on coherent FFH/DS, and we have shown that, if spectral sensing mechanism for MTI frequency and power monitoring is available, the MTI in FFH/DS reception is a set of complex sinusoid components with deterministic amplitudes and random phases, instead of the conventionally assumed Gaussian random variables. In light of this new finding, a novel combining method is proposed. It utilizes the spectral sensing information to adaptively compute the combining weights, following Maximum Signal to Interference plus Noise (MSINR) law. Its combining performance is analyzed and compared with other existing methods, and verified by simulations. It is shown that the proposed adaptive MSINR combining has satisfactory performance under both medium and strong MTI scenarios.

No abstract