In this article, we study the advantages and disadvantages that full-duplex (FD) radio technology brings to remote-controlled drone and counter-drone systems in comparison to classical half-duplex (HD) radio technology. We consider especially the physical-layer reliability perspective that has not yet been comprehensively studied. For establishing a solid analytical background, we first derive original closed-form expressions to evaluate demodulation and detection performance of frequency-hopped and frequency-shift keyed drone remote control signals under external or self-inflicted interference. The developed analytical tools are verified by comparison to simulated results and then used to study the impact that the operation mode has on the operable area of drones and effectiveness of counter-drone systems in different scenarios, linking the physical layer performance to practical safety. Analysis of the scenarios shows that FD operation compared to HD can improve the effectiveness of a counter-drone system and that in FD mode a drone can detect the attacks from the counter-drone system from a greater distance than in HD mode. However, two-way communication between the remote controller and drone in FD mode compared to HD significantly reduces the drone’s operable area when targeted by a smart counter-drone system.

Cognitive jammers are able to deploy advanced strategies that degrade the performance of cognitive radio (CR) user communications. In this study, the authors study the problem of power allocation in CR user and jammer games, over parallel Gaussian channels. They model the interaction between a communicator (a transmitter–receiver pair) and a jammer using zero‐sum games with continuous action sets; they describe unilateral, Nash and Stackelberg games. They compare the Nash equilibrium (NE), the Stackelberg equilibrium and the minmax/maxmin optimal power allocations through the simulation of the diverse game scenarios. Finally, they give the theoretical proof of existence and uniqueness of the NE.

In this letter, analytical expressions are derived for the power spectral density (PSD) of orthogonal frequency division multiplex (OFDM) signals employing a cyclic prefix (CP-OFDM) or zero padding (ZP-OFDM) time guard interval. Under the relatively weak assumptions that (i) the data are independent and identically distributed on all OFDM subcarriers and (ii) the OFDM pulse shape is sufficiently localized in time, simple closed-form PSD expressions can be obtained. These expressions are then compared to existing OFDM PSD expressions and validated by inspecting the power spectra of some standardized OFDM signals.

In xDSL systems, crosstalk can be separated into two categories, namely in-domain crosstalk and out-of-domain crosstalk. In-domain crosstalk is also referred to as self crosstalk. Out-of-domain crosstalk is crosstalk originating from outside the multi-pair system and is also denoted as external noise (alien crosstalk, radio frequency interference,...). While self crosstalk in itself can easily be canceled by a linear detector like the ZF detector, the presence of external noise requires a more advanced processing. Coordination between transmitters and receivers enables the self crosstalk and the external noise to be mitigated using MIMO signal processing, usually by means of a whitening filter and SVD. In this paper, we investigate the problem of finding the optimal power allocation in MIMO xDSL systems in the presence of self crosstalk and external noise. Optimal Tx/Rx structures and power allocation algorithms will be devised under practical limitations from xDSL systems, namely per-modem total power constraints and/or spectral mask constraints, leading to a generalized SVD-based transmission. Simulation results are given for bonded VDSL2 systems with external noise coming from ADSL2+ or VDSL2 disturbing lines, along with a comparison between algorithms with one-sided signal coordination either only at the transmit side or the receive side.

In xDSL systems, in-domain crosstalk is easily dealt with based on zero-forcing receiver or precoding while out of domain or alien crosstalk requires a more advanced processing. In vector channels, multiple input multiple output (MIMO) signal processing mitigates both types of crosstalk, usually by means of a pre-whitening filter, singular value decomposition (SVD) based transmission and waterfilling based power allocation. In this paper, we investigate the problem of power allocation in xDSL vector channels under in-domain and alien crosstalk. We propose a new power allocation algorithm to maximize the MIMO capacity under per-modem total power constraints and spectral mask constraints, leading to a generalized SVD-based transmission.

Linear precoded OFDM systems with channel coding have already been demonstrated to efficiently exploit frequency and time diversities of the transmission channel. Iterative receivers which iteratively perform channel decoding and deprecoding provide very good performance. In the literature, these iterative receivers are based on maximum likelihood based functions for both linear deprecoding and channel decoding leading to a high complexity for large size of preceding matrices or high modulation order. In this paper, a simple linear operation instead of a maximum likelihood based one is carried out for deprecoding allowing the use of large preceding matrices and thus an optimal exploitation of the signal diversity.

In this paper, the combination of spatial multiplexing with coded multi-carrier code division multiplex access (MC-CDMA) for a multiple input multiple output (MIMO) Rayleigh fading multipath channel is considered. A practical receiver structure performing the iteratively MIMO detection, multi-user despreading and channel decoding is presented. The MIMO detector, employing a linear minimum mean square error (MMSE) parallel soft interference canceller (PSIC) equalizer, allows to cope with the co-antenna interference (CAI). Simulation results show the efficiency of the iterative receiver for spatial multiplexed coded MC-CDMA that brings spatial diversity, increasing data rate, and multi-user flexibility.