Abstract Unmanned aerial vehicles (UAVs) are widely considered as key enablers for future wireless networks due to their advantages, such as high mobility and flexible deployment. In this paper, the UAV assisted secure communication system is investigated, where the UAV is deployed as the mobile jammer to prevent the eavesdropper from overhearing the confidential message. With the objective of maximizing the secrecy rate, a joint optimization problem involving the trajectory and transmit power of UAV, as well as the transmit power of source node is formulated. Moreover, the effects of Non‐Fly Zone (NFZ) and imperfect estimation on the location of eavesdropper are also taken into consideration. As the original problem is hardly trackable, the worst case secrecy rate (WCSR) assumption is first employed to bypass the uncertainty brought by the estimation error. Then a block coordinate descent (BCD) based algorithm is proposed to decompose the problem into three sub‐ones, where the trajectory of UAV, the transmit power of UAV and the transmit power of source can be obtained in an iterative manner. Simulation results reveal that the proposed algorithm can improve the secrecy performance significantly. In addition, the robustness of the proposed algorithm under the estimation error can also be verified.

In this paper, we propose the quality-of-service (QoS) driven robust power allocation policy with channel uncertainty in the secure multicarrier full-duplex (FD) relay communication system, where the statistical delay QoS is given by the secure effective capacity (SEC). To maximize the SEC under the constraints of both the total system power and the residual loopback interference (LI) power of the FD relay, an optimization problem is formulated and the corresponding power allocation strategy has been presented in the case of perfect channel state information (CSI) and imperfect CSI. Specially, considering the imperfect CSI, we propose a robust power allocation scheme, where the channel uncertainty is modeled by a bounded region. Furthermore, the worst-case method and the Bernstein approximations are utilized to deal with the uncertainty. After the Taylor approximation based simplification of the formulated optimization problem, the optimal solution is obtained by subgradient descent algorithm based on Lagrangian dual method and Karush-Kuhn-Tucker (KKT) conditions. With known error range of CSI, numerical results and analysis illustrate that the proposed robust power allocation strategy can satisfy the statistical delay QoS requirement very well. Furthermore, the trade-off between the SEC and the robustness can be achieved with channel uncertainty.

Robust quality-of-service (QoS)-based and secrecy rate-based secure transmission designs are investigated for a multiple-input single-output system with multiple eavesdroppers and a cooperative jammer. Two scenarios are considered: (a) eavesdroppers' channel state information (ECSI) is available and (b) ECSI is unavailable. In scenario (a), a QoS-based design is considered to minimize the worst case signal-to-interference-and-noise ratio at the eavesdroppers and to guarantee the QoS of the legitimate receiver. A secrecy rate-based design is also studied where the worst case secrecy rate is maximized. In scenario (b), a QoS-based design is considered to maximize the power of jamming signals under the QoS constraint of the legitimate receiver, and the secrecy rate-based design is not applicable. In all these designs, we jointly optimize the transmit beamforming vector and the covariance matrix of jamming signals under individual power constraints. As the optimization problems are non-convex, we propose an algorithm for each problem through semidefinite relaxation. Our analysis and simulation results show that, even though the linear precoding scheme in our designs is transmit beamforming rather than the general rank transmit covariance, this does not cause any loss of optimality.

We investigate a secure multiuser time division multiple access (TDMA) system with statistical delay quality of service (QoS) guarantee in terms of secure effective capacity. An optimal resource allocation policy is proposed to minimize theβ‐fair cost function of the average user power under the individual QoS constraint, which also balances the energy efficiency and fairness among the users. First, convex optimization problems associated with the resource allocation policy are formulated. Then, a subgradient iteration algorithm based on the Lagrangian duality theory and the dual decomposition theory is employed to approach the global optimal solutions. Furthermore, considering the practical channel conditions, we develop a stochastic subgradient iteration algorithm which is capable of dynamically learning the intended wireless channels and acquiring the global optimal solution. It is shown that the proposed optimal resource allocation policy depends on the delay QoS requirement and the channel conditions. The optimal policy can save more power and achieve the balance of the energy efficiency and the fairness compared with the other resource allocation policies.

In this paper, we investigate the power allocation policy for an underlay secure cognitive radio (CR) system with statistical delay quality-of-service (QoS) guarantees. The objective is to maximize the secure effective capacity of the secondary user (SU) in CR system, which represents the maximum secrecy constant arrival rate with delay QoS requirements for the secrecy system. The constrains include the average transmission power of the SU and the interference power to the PU. Both the average interference power and the peak interference power are taken into account in the problem formulation. A closed-form power allocation scheme is derived via employing the Lagrangian dual method and the Karush-Kuhn-Tucker optimization conditions. It is shown that the fading states of the wiretap channel and the peak interference power to the PU have significant impacts on the QoS driven power adaptation. Simulation results demonstrate that our proposed power policy outperforms other policies in improving the system throughput with delay QoS guarantees, especially when the delay QoS requirement is strict.

This paper studies a cooperative cognitive radio network (CRN), where the primary system leases the licensed band to the secondary system for a fraction of time in exchange for the secondary user (SU) acting as a decode-and-forward relay. Our aim is to determine the cooperative resource allocation strategy among the primary user (PU) and SU so as to minimize both the total power consumption and the leased time. Considering the delay-sensitive applications in CRN, the proposed policy ensures delay-related quality-of-service (QoS) requirements of both PU and SU. To this end, a multi-objective optimization problem of power and time allocation is formulated based on the effective capacity. Via employing weighting method the optimization problem is transformed to a convex one and solved based on the lagrangian dual method. The proposed policy has been shown to be deterministic functions of delay QoS exponent and channel fading states. In particular, the power allocation is achieved by multi-level QoS based water-filling policy. Moreover, numerical results are provided to demonstrate the performance of the proposed resource allocation policy.

A novel Gaussian approximation algorithm is proposed for calculating the thresholds of low-density parity- check (LDPC) code ensembles under sum-product decoding. The updating rules of means and error probability are derived. Numerical results show that the thresholds obtained by the proposed algorithm closely coincide with the values computed by density evolution (DE). Moreover, our algorithm can calculate the thresholds of irregular LDPC codes with higher accuracy than the algorithm proposed by Lehmann and Maggio.

In this paper, we propose a scheme to design unequal error protection low-density parity-check (UEP-LDPC) codes based on Gaussian approximation algorithm over AWGN channel. Using this method, we can find effective UEP-LDPC code ensemble which has good overall performance and good UEP property. Simulation results show the superiority of the proposed UEP-LDPC code in improving the quality of reconstructed image in uncompressed image and set partitioning into hierarchical trees (SPIHT) coded image transmission.

If the degree distribution is chosen carefully, the irregular LDPC codes can outperform the regular ones. In this paper, we proposed an LDPC coded BICM scheme in image transmission system to improve both efficiency and reliability. Simulation results show that LDPC codes are good coding schemes over fading channel in image communication. Simultaneously, irregular codes can obtain a code gain of about 0.7 dB than regular ones when BER is 10/sup -4/. So the irregular LDPC codes are more suitable for image transmission than the regular codes.

This paper investigates a low-density parity-check (LDPC) coded orthogonal frequency-division multiplexing (OFDM) wireless communication system based on IEEE 802.11a standard. And an initialization algorithm is proposed for the decoding of LDPC coded modulation in OFDM system. The LDPC decoding procedure is simplified without the estimation of channel noise power. Simulation results show that this algorithm is effective and the decoding performance is satisfied when maximum iteration number is 10.

As a class of block codes, LDPC codes with any desired code rate and code length are easily constructed. We examine the performance of three high-rate (0.769, 0.889, 0.935) LDPC codes in image transmission. Simulation results show that LDPC codes are good coding schemes over fading channels in image communication with lower system complexity. The distorted images can be recovered by using the three high-rate LDPC codes at SNR of 10 dB, 11.5 dB and 14 dB respectively. These high-rate codes can achieve relatively higher bandwidth efficiency than the low-rate codes can. Moreover, we discovered that the code rate has more influence on the performance than the code length does.

A new scheme is proposed about how to make use of the unequal error protection (UEP) property of irregular low-density parity-check (LDPC) codes. By means of the construction of a weight-increasing parity-check matrix and systematic encoding, the mapping between the important information data and the elite bits of an irregular LDPC code becomes traceable and tractable. Thus, the inherent UEP property of irregular LDPC codes is not the theoretical interest any more. The proposed scheme makes it practical to implement UEP in system applications. Taking an irregular LDPC code with code length 10000 and code rate one half as an example, simulation results are presented over AWGN channels. The validity of the proposed scheme is verified by simulation.

Low-density parity check coded bit-interleaved coded modulation (BICM) schemes are analyzed in this paper. A simplified decoding method without iteration between demodulator and decoder is provided. And the performance over additive white Gaussian noise (AWGN) and Rayleigh fading channels are analyzed. Through the simulation results we can conclude that the schemes with low complexity decoding method have good performance both over AWGN and Rayleigh fading channels.