Interference-resilient spectrum sharing with collision detection and data recovery for cognitive radio networks

To promote reliable and secure communications in the cognitive radio network, the automatic modulation classification algorithms have been mainly proposed to estimate a single modulation. In this paper, we address the classification of superimposed modulations dedicated to 5G multiple-input multiple-output (MIMO) two-way cognitive relay network in realistic channels modeled with Nakagami- distribution. Our purpose consists of classifying pairs of users modulations from superimposed signals. To achieve this goal, we apply the higher-order statistics in conjunction with the MultiBoostAB classifier. We use several efficiency metrics including the true positive (TP) rate, false positive (FP) rate, precision, recall, F-Measure and receiver operating characteristic (ROC) area in order to evaluate the performance of the proposed algorithm in terms of correct superimposed modulations classification. Computer simulations prove that our proposal allows obtaining a good probability of classification for ten superimposed modulations at a low signal-to-noise ratio, including the worst case (i.e., ), where the fading distribution follows a one-sided Gaussian distribution. We also carry out a comparative study between our proposal using MultiBoostAB classifier with the decision tree (J48) classifier. Simulation results show that the performance of MultiBoostAB on the superimposed modulations classifications outperforms the one of J48 classifier. In addition, we study the impact of the symbols number, path loss exponent and relay position on the performance of the proposed automatic classification superimposed modulations in terms of probability of correct classification. 

Automatic Classification of Superimposed Modulations for 5G MIMO Two-Way Cognitive Relay Networks

This paper considers a cellular multiple-input single- output (MISO) system overheard by multiple eavesdroppers, in the presence of one pair of single- antenna device-to-device (D2D) nodes working as an underlay. The D2D nodes are permitted to access the cellular channel for their own communications. We assume that the channel state information (CSI) on all links is imperfect, and more specifically, the CSI error follows an arbitrary distribution with only the first and second moments available at the transmitter. Our goal is to design the covariances of confidential message and artificial noise, as well as the transmit power at the D2D transmitter, such that the total consumed power is minimized subject to a sequence of worst-case outage constraints on the received signal- to-interference-plus-noise ratio (SINR) at each receiver. The worst-case outage constraints are imposed to satisfy SINR outage requirement under arbitrarily distributed CSI uncertainty. The resulting problem is challenging to solve due to its inherently complex structure. However, we reveal its hidden convexity by carrying out a duality-based reformulation. Then it is proved that the proposed method always yield a single- stream beamforming solution. The complexity analysis of our proposed method is also presented. Finally, the efficacy of the proposed design is demonstrated by simulations.

Outage-Constrained Secure D2D Underlay Communication with Arbitrarily Distributed CSI Uncertainty

Physical layer network coding (PNC) is combined with multiple antennas to increase the spectral efficiency of wireless communication systems. In this work, we present a PNC framework including both uplink and downlink for binary phase shift keying (BPSK). In the uplink, we propose a scheme for detecting network-coded symbol (NCS) with reduced complexity. For the downlink, we propose a transmission scheme of NCS through maximum ratio transmission (MRT) by defining the precoding vector as an average of users’ channels. The bit-error-rate (BER) performances and the comparison results with the conventional scheme in both downlink and uplink are provided for the proposed lowcomplexity PNC framework.

A Framework for Physical Layer Network Coding with Multiple Antennas for BPSK

In this paper, We propose a novel power allocation scheme for physical-layer network coding (PNC) in uplink multi-way relay channels (MWRC). The power allocation is formulated as a constrained optimization problem under the transmitting power constraint of user terminals, aiming at maximizing the success probability of the successive interference cancellation (SIC) detection at the relay. optimizing over such a metric maximizes the probability of correctly detecting all user signals, which is critical to the network code generation at the relay. Specifically, We first develop a generalized closed-form success probability of the SIC detection on signals with pulse-amplitude modulation (PAM) at the relay. A constraint optimization is formulated over this probability subject to the poWer constraints of user terminals. We implement an evolutionary particle swarm optimization (PSO) algorithm to solve the problem whose cost function is complicated and not necessarily concave. The numerical results show that the proposed power allocation method can improve the quality of network code extraction at the relay.

Optimal Power Allocation Based on Success Probability of SIC Detection in MWRC PNC

In this paper, we propose a novel scheme for physical-layer network coding (PNC) in multiway relay channels (MWRC) from the perspective of sequential multiuser detection. We consider an uplink MWRC scenario where <inline-formula> <tex-math notation=\"LaTeX\">$N$ </tex-math></inline-formula> users, each equipped with a single antenna, simultaneously transmit their signal to a relay equipped with <inline-formula> <tex-math notation=\"LaTeX\">$K$ </tex-math></inline-formula> antennas (<inline-formula> <tex-math notation=\"LaTeX\">$K < N$ </tex-math></inline-formula>). Extraction of the network codes from the superimposed user signals at the relay node is formulated as an under-determined linear system. To solve this problem with low decoding complexity, the proposed method combines successive interference cancellation (SIC) with Babai estimation for regularized integer least squares (ILS). Specifically, SIC decoding is first employed to detect a selected subset of stronger user signals and remove their interfering effects. Babai estimation is then applied to extract the remaining user signals, which is formulated as an ILS problem with reduced dimension. We develop a power allocation scheme to enhance the performance of both SIC and ILS steps, and discuss an optimal user pairing strategy based on the average decoding error probability. Numerical results demonstrate the performance improvement of the proposed method in extracting network codes from multiple superimposed user signals.

/pdf/efficient-detection-scheme-for-physical-layer-network-coding-5cvcc96ds6.pdf

Efficient Detection Scheme for Physical-Layer Network Coding in Multiway Relay Channels

In this paper, we investigate the physical-layer network coding (PNC) scheme based on successive interference cancellation (SIC) in multi-way relay channels (MWRC). We consider a scenario where all users simultaneously transmit signals to the relay in the up-link stage while the relay broadcasts a coded message in the down-link stage. In order to extract the network codes from superimposed signals and guarantee a low decoding complexity, we propose a novel SIC scheme at the relay node to iteratively estimate the signals from all users. A Max-Min strategy is introduced as an optimal solution to power allocation among users to ensure accurate estimation in the SIC process. In addition, to further improve the system performance, an optimal strategy that decides the coding rule is developed by considering the error probability of the SIC process. Simulation results demonstrate the performance improvement of the proposed SIC aided PNC technique when used in conjunction with the optimal power allocation and coding rule in multi-way relay channels.

SIC aided physical-layer network coding for multi-way relay channels

In this paper, we study the problem of joint multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying and artificial noise (AN) optimization for secure communication between a source-destination pair in the presence of multiple eavesdroppers (eves). The eves' channel state information (ECSI) is subject to arbitrarily distributed random errors. Assuming that only the first and second moments of the ECSI errors are known, we introduce a probabilistically robust design method, which aims to maximize the received signal-to-interference-plus-noise ratio (SINR) at the destination while satisfying a set of robust intercept probability constraints. Since the resultant optimization problem is non-convex, we propose a solution approach by resorting to a duality-based method along with the semidefinite relaxation (SDR) technique, where a global optimal solution to our design problem can be found. Our simulation results demonstrate the improved secrecy of the proposed robust relaying design against eavesdropping and its robustness against the channel uncertainties.

Intercept probability-constrained secure MIMO AF relaying with arbitrarily distributed ECSI errors

In this paper, we propose a novel power allocation scheme for physical-layer network coding (PNC) in downlink multi-way relay channels (MWRC). The power allocation is formulated as a constrained optimization problem, where the aim is to maximize the success probability under a total power constraint when using Babai estimation for signal detection. Optimizing over this metric allows us to maximize the probability of successfully decoding a chain of network codes, which is of crucial importance in downlink multi-way PNC. Specifically, to meet the different requirements for transmission quality in applications, we consider different aggregate measures of success probability over the participating user terminals, i.e., the arithmetic mean, the geometric mean, and the maximin. For each measure, we formulate a constrained optimization and demonstrate the concavity of the objective, allowing us to obtain solution efficiently via iterative means. The performance of the proposed power allocation schemes for downlink PNC in MWRC is evaluated by means of computer simulations over Raylegih fading channels. The results demonstrate the effectiveness of the proposed schemes in improving the success probability in the reception of a chain of network codes.

Hao Li

Papers

Efficient Detection Scheme for Physical-Layer Network Coding in Multiway Relay Channels

SIC aided physical-layer network coding for multi-way relay channels

Intercept probability-constrained secure MIMO AF relaying with arbitrarily distributed ECSI errors

Success-Probability-Based Power Allocation for Downlink PNC in Multi-way Relay Channels