Individual Power Constraints Research Articles

Robust MISO Beamforming With Cooperative Jamming for Secure Transmission From Perspectives of QoS and Secrecy Rate

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.

Robust Transceiver Design in Full-Duplex MIMO Cognitive Radios

We consider a full duplex (FD) multiple-input multiple-output (MIMO) underlay cognitive radio cellular network, in which an FD secondary base-station (BS) serves multiple half-duplex uplink (UL) and downlink secondary users (SUs) at the same time and frequency. We assume that the channel state information (CSI) available at the transmitters is imperfect, and the errors of the CSI are assumed to be norm bounded. Under the impact of channel uncertainty, we address the sum mean-squared-errors minimization problem subject to individual power constraints at the UL SUs, a total power-constraint at the secondary BS, and the interference constraints on the primary users by the secondary network. By transforming the problem into an equivalent semidefinite programming (SDP), we propose an iterative alternating algorithm to compute the transceiver matrices jointly. Moreover, to reduce the high computational complexity of the SDP method, we develop a cutting-set method, which solves the problem by alternating between an optimization step (transceiver design) and a pessimization step (worst-case channel analysis). Numerical results are presented to show the effectiveness and robustness of the proposed algorithms.

Power allocation under global and individual power constraints for full‐duplex relay networks

In this study, the authors propose a power allocation strategy for full-duplex relay (FDR) networks, where two cases are considered according to whether the direct link is desired or not. The power allocation is studied in two scenes under the amplify-and-forward and decode-and-forward protocols, respectively. Aiming at maximising the system capacity, the authors derive the optimal power allocation strategy under the condition that the source and relay have the same maximum power constraint and the total power is limited. The effects of global and individual power constraints for FDR on system capacity are analysed. Simulations verify the theoretical analysis and indicate that the proposed power allocation strategy enhances the system performance greatly compared with uniform power allocation.

Transmit power optimization for relay-aided multi-carrier D2D communication

In this paper, we consider the power optimization problem in Orthogonal Frequency Division Multiplexing (OFDM)-based relay-enhanced device-to-device (D2D) communication. In a single cell transmission scenario, dualhop communication is assumed in which each D2D user re-uses the spectrum of just one Cellular User (CU). In this work, we formulate a joint optimization scheme under a Decode-and-Forward (DF) relaying protocol to maximize the sum throughput of D2D and cellular networks via power allocation over different sub-carriers. The problem is thus transformed into a standard convex optimization, subject to individual power constraints at different transmitting nodes. We exploit the duality theory to decompose the problem into several sub-problems and use Karush-Kuhn- Tucker (KKT) conditions to solve each sub-problem. We provide simulation results to validate the performance of our proposed scheme.

Transmission completion time minimization in digital network coding assisted two-way relay OFDM networks

This paper investigates the two-way relay transmission over orthogonal frequency division multiplexing (OFDM) channels using digital network coding. For a given amount of data to be transmitted, we formulate an optimization problem to minimize the total transmission completion time by jointly allocating the power and assigning the subcarriers under individual power constraints. Due to the difficulty to derive the explicit solution to this optimization problem, we decompose it into two subproblems. Then, we design suboptimal algorithms with low complexity for the two subproblems, where subcarriers are assigned firstly and then the power is optimally allocated over the assigned subcarriers. The end-to-end delay is adopted to evaluate the system in a systematic view. Simulation results show that our proposed scheme achieves less than 1.06 times the minimal total transmission completion time achieved by exhaustive search for two-way relay OFDM systems and outperforms non-network coding schemes with a probability over 90%. Moreover, the corresponding distribution regions with performance gain are also discussed by simulations, which may give some insights in the application of network coding in OFDM systems.

Cooperative Interference and Power Allocation in a Bidirectional Untrusted Relay Network With Channel Estimation Errors

The secure communication of a two-way untrusted amplify-and-forward relay network under the imperfect channel state information is investigated. To improve the secrecy of the relay wiretap system, artificial noise is introduced into each source signal. The total and the individual power constraint conditions are considered. To maximize the attainable secrecy rate, an iterative power allocation algorithm is designed under the total power constraint. As a more practical system design, a suboptimal power allocation scheme is proposed. For the sake of comparison, the security performances of the noncooperative interference strategy and the one-way cooperative interference strategy are also investigated. Simulation results demonstrate that the proposed bidirectional cooperative interference schemes perform better in the secrecy rate of communication system.

Resource allocation for OFDM‐based improved DF relaying

This study considers an improved decode and forward (DF) protocol in an orthogonal frequency division multiplexing-based cooperative system, where the improved DF protocol implies that the source node is allowed to emit the same symbol in the second phase as that in the first phase, irrespective to whether the relay is idle or not. Because rate provision is one of the main design goals in wireless network, the authors construct an optimisation problem to improve the overall sum rate of the system and propose a joint power allocation and subcarrier pairing algorithm. Total power constraint and individual power constraints at the source node and the relay node will be treated differently. Both theoretical analysis and simulation results demonstrate that the authors' proposed joint algorithm for the improved DF protocol drastically harvests remarkable gains from the extra repeat transmission in the second phase and is superior to other existing methods.

On Non-Orthogonal Multiple Access With Finite-Alphabet Inputs in Z-Channels

This paper focuses on the design of non-orthogonal multiple access in a classical two-transmitter two-receiver Z-channel, wherein one transmitter sends information to its intended receiver from the direct link while the other transmitter sends information to both receivers from the direct and cross links. Unlike most existing designs using (continuous) Gaussian input distribution, we consider the practical finite-alphabet (i.e., discrete) inputs by assuming that the widely used quadrature amplitude modulation constellations are adopted by both transmitters. To balance the error performance of two receivers, we apply the max–min fairness design criterion in this paper. More specifically, we propose to jointly optimize the scaling factors at both transmitters, which control the minimum Euclidean distance of transmitting constellations, to maximize the smaller minimum Euclidean distance of two resulting constellations at the receivers, subject to an individual average power constraint at each transmitter. The formulated problem is a mixed continuous-discrete optimization problem and is thus intractable in general. By resorting to the Farey sequence, we manage to attain the closed-form expression for the optimal solution to the formulated problem. This is achieved by dividing the overall feasible region of the original optimization problem into a finite number of sub-intervals and deriving the optimal solution in each sub-interval. Through carefully observing the structure of the optimal solutions in all sub-intervals, we obtain compact and closed-form expressions for the optimal solutions to the original problem in three possible scenarios defined by the relative strength of the cross link. Simulation studies are provided to validate our analysis and demonstrate the merits of the proposed design over existing orthogonal or non-orthogonal schemes.

Artificial noise–aided secure communication in a bidirectional relaying network

SummaryAn artificial noise strategy is proposed for amplify‐and‐forward bi‐directional relay network where the eavesdropper can wiretap the relay channels in both hops. Artificial noise is used to confuse the eavesdropper and improve its secrecy. Specifically, the source and the relay are allowed to split their available transmit power into 2 parts: a useful information portion and a jamming portion to transmit a jamming signal. The mathematical model is established for 2‐way relay network with an eavesdropper. The secrecy rate achieved by using artificial jamming is derived from the above model. The optimal power allocation with individual power constraint is obtained via sequential quadratic programming to maximize the secrecy sum rate, and 2 special cases are investigated. Furthermore, the benchmark is provided for the purpose of performance comparison. Simulation results show that the proposed strategy can significantly improve the secrecy sum rate by using artificial noise to jam the eavesdropper.

On the Optimal Power Allocation for Two-Way Full-Duplex AF Relay Networks

This paper investigates the optimal power allocation that maximizes the system utility for a full-duplex (FD) amplify-and-forward (AF) two-way relay network (TWRN) with a rate outage and a power constraint. Both cases of an individual and a sum power constraint are considered. To formulate the corresponding optimization problem, closed-form expressions of outage probabilities are needed. With FD transceivers, the derivation of such closed-form expressions become too involved. Thus, approximate closed-form expressions were derived instead. The resulting optimization problem is still nonconvex and difficult to solve. Via solving a series of approximate convex problems, a successive convex approximation (SCA) algorithm was proposed. Our simulation results demonstrate the accuracy of the approximate closed-form expressions of outage probabilities and that the proposed SCA algorithm achieves near-optimal performance and significantly outperforms the full power allocation under the individual power constraint and uniform power allocation under the sum power constraint both in system utility and in power consumption. Our results further show that simultaneous power transmission for all relay nodes with judicious power allocation generated by the SCA algorithm achieves $174\%$ of performance gain under the individual power constraint, and $85 \%$ of performance gain under the sum power constraint over the relay selection scheme. A tradeoff between the FD system and the half-duplex (HD) system with respect to the residual interference was also observed. We can also observe that not only the residual self-interference but also the cross-link interference is a factor that degrades the system performance for an FD system.

Fronthaul-Limited Uplink OFDMA in Ultra-Dense CRAN With Hybrid Decoding

In an ultra-dense cloud radio access network (UD-CRAN), a large number of remote radio heads (RRHs), typically employed as simple relay nodes, are distributed in a target area, which could even outnumber their served users. However, one major challenge is that the large amount of information required to be transferred between each RRH and the central processor (CP) for joint signal processing can easily exceed the capacity of the fronthaul links connecting them. This motivates our study in this paper on a new hybrid decoding scheme where in addition to quantizing and forwarding the received signals for joint decoding at the CP, i.e. forward-and-decode (FaD) as in the conventional CRAN, the RRHs can locally decode-and-forward (DaF) the user messages to save the fronthaul capacity. In particular, we consider the uplink transmission in an orthogonal frequency division multiple access (OFDMA)-based UD-CRAN, where the proposed hybrid decoding is performed on each OFDMA sub-channel (SC). We study a joint optimization of the processing mode selections (DaF or FaD), user-SC assignments and the users' transmit power allocations over all SCs to maximize their weighted-sum-rate subject to the RRHs' individual fronthaul capacity constraints and the users' individual power constraints. Although the problem is non-convex, we propose a Lagrange duality based solution, which can be efficiently computed with good accuracy. Further, we propose a low-complexity greedy algorithm which is shown to achieve close to the optimal performance under practical setups. Simulation results show the promising throughput gains of the proposed designs with hybrid decoding, compared to the existing schemes that perform either DaF or FaD at all SCs.

Utility Maximization for Two-Way AF Relaying Under Rate Outage Constraints

In this paper, we focus on maximizing the system utility (e.g., the weighted sum-rate, weighted geometric mean rate, and the harmonic mean rate) of a two-way relay network (TWRN) from the outage probability perspective; a TWRN has multiple relay nodes and two terminal nodes. We assume amplify-and-forward relaying with analog network coding protocol and half-duplex transmission with perfect channel state information at the receiver ends and channel distribution information at the transmitter ends. We derive the approximated closed-form for the outage probability of a TWRN; however, the approximated outage constraints lead to a non-convex structure for the considered problem. Based on the successive convex approximation technique, we obtain near optimal solution for the non-convex problem. Moreover, we derive closed-form solutions for the maximization problem for the weighted sum rate maximization problem for a TWRN with a single relay node and two relay nodes under individual power constraints. Our simulation results demonstrate the accuracy of our outage probability approximation model and the advantages of our algorithm over naive methods of full and uniform power allocation.

Power saving transmission in interference networks

This study proposes a power control scheme to obtain minimum aggregate power in a system composing of interfering links (N-link) while a target sum-rate is met. The authors develop an analytical framework for two interfering links which results in the optimal transmission policy. For N > 2, they propose a suboptimal solution based on successive convex approximation for low-complexity (SCALE) algorithm. They modify the SCALE algorithm to converge to a point satisfying Karush–Kuhn–Tucker conditions when high signal-to-noise-and-interference approximation of rate function is not valid. They also provide a suboptimal solution based on the geometric programming. They perform numerical evaluations in a dense interference environment and compare the performance of the modified SCALE with that of the SCALE algorithm. They also compare the performance of proposed power control with that of sum-rate maximisation of interfering links, in which the individual power constraint on each user is considered. The simulation results indicate that the modified SCALE performs better than the SCALE algorithm. The results also demonstrate that the proposed power control can save power comparing to the sum-rate maximisation in most considered cases.

Coordinated Multicell Multicast Beamforming Based on Manifold Optimization

Multicast beamforming is a key technology for next-generation wireless cellular networks to support high-rate content distribution services. In this paper, the coordinated downlink multicast beamforming design in multicell networks is considered. The goal is to maximize the minimum signal-to-interference-plus-noise ratio of all users under individual base station power constraints. We exploit the fractional form of the objective function and geometric properties of the con-straints to reformulate the problem as a parametric manifold optimization program. Afterwards we propose a low-complexity Dinkelbach-type algorithm combined with adaptive exponential smoothing and Riemannian conjugate gradient iteration, which is guaranteed to converge. Numerical experiments show that the proposed algorithm outperforms the existing SDP-based method and DC-programming-based method and achieves near-optimal performance.

Distributed Beamforming in MISO SWIPT System

In previous works on simultaneous wireless information and power transfer (SWIPT) multiple-input single-output (MISO) system with multiple users, beamforming requires all the transmitters know the channel state information (CSI) of the whole system. We relax it so that it is a practical assumption: Each transmitter only knows its own CSI to all the receivers, combined with individual power constraints at transmitters and signal-to-interference-plus-noise ratio (SINR) constraints at information receivers. The objective is to maximize the total harvested energy at the energy receivers. An improved version of the alternating direction method of multipliers is proposed. In particular, we split an optimization problem with nonconvex constraints into iterations of several singular value decomposition (SVD) problems and prove the convergence. Simulation results show that our algorithm achieves less computational complexity and control channel budget with acceptable performance degradation when compared with a centralized solution.

Resource Allocation in Secure Multicarrier AF Relay System Under Individual Power Constraints

We consider a dual-hop amplify-and-forward (AF) relay-aided multicarrier system between a source and destination, in which there is an external eavesdropper which taps the signals in both hops. We consider individual power constraints at source and relay. The relay pairs the carriers in the second hop and enhances the system sum rate through multicarrier diversity. The sum rate maximization problem belongs to the class of mixed-integer nonlinear program (MINLP) due to the variables corresponding to subcarrier (SC) pairing being binary and its joint optimization with source and relay powers. We propose a solution based on alternate maximization and show that it converges to a local maximum. We also derive a computationally less complex and optimally computable solution based on transforming the problem to a single power variable which, ultimately, is a lower bound to sum rate. We analyze both the solutions when either the source power or relay power, or both, are very high. In the process, we also derive asymptotically achievable upper bound to the sum rate. We also show that either full relay power or full source power, or both, are used at the optimal point. Our numerical results demonstrate an improved sum rate over a scenario of no pairing at relay.

Optimal power allocation for a full-duplex multicarrier decode-forward relay system with or without direct link

This paper addresses power allocation problems for a dual-hop full-duplex multicarrier decode-forward relay system with or without a direct link from the source to the destination. The full-duplex relay has a residual self-interference proportional to its transmitted power. We consider two schemes of decode-forward at the relay: carrier-wise decode-forward (CDF) and group-wise decode-forward (GDF). For the CDF scheme, we consider problems of optimal power allocation subject to system-wise total power constraint, node-wise individual power constraint and system-wise rate constraint, respectively. All these problems are shown to be equivalent to convex problems, and fast algorithms for finding the exact solutions are developed. For the GDF scheme, we focus on the case of node-wise individual power constraint. This problem is non-convex for which we develop fast algorithms for finding locally optimal solutions. Using the algorithms developed in this paper, we are able to show that the system capacity with optimal power allocation based on either CDF or GDF is higher than that of the half-duplex relay (HDR) system at power levels where HDR outperforms the direct transmission via the direct link. Furthermore, the system capacity based on GDF is consistently higher than that of HDR for all power levels while both have the same degree of freedom. This paper also shows new insights of algorithmic development, which should be useful for other related problems.

Analysis of capacity limits over fading environment with imperfect channel state information for cognitive radio network

In this paper, we have explored an optimal power allocation scheme for the spectrum sharing with imperfect channel state information between the cognitive/secondary user (CU) and licensed/primary user (PU) in the Rayleigh fading environment. We have analyzed the ergodic capacity of CU link under the combination of peak transmit power and peak/average interference power constraints with or without the primary user interference. In addition to this, the outage capacity with multiple primary users’ interference is also analyzed with the error variance under the joint peak transmit power and peak interference power constraint as well as individual peak interference power constraint. Moreover, the power disbursement is also investigated to achieve the lower limit of ergodic and outage capacity. The minimum mean square channel estimation technique is used for the channel estimation between CU and PU. Further, the convex optimization method is used for the optimal power allocation.

SER Optimization of OFDM Based AF Relaying in the Presence of AWGGN

This paper studies joint power allocation and subcarrier pairing strategies for an orthogonal frequency division multiplexing-based amplify and forward relay system. The optimization target function is symbol error rate (SER) in the context of an additive white generalized Gaussian noise (AWGGN), which encompasses numerous noise types. For instance, the familiar additive white Gaussian noise (AWGN) is just a special case of AWGGN. At a given data rate, the SER performance is optimized under total and individual power constraints, respectively. Simulation results demonstrate superior performance gap through our adaptive resource allocation approach over equal power allocation as well as fixed subcarrier pairing strategies. The impacts of practical issues on the SER performance, such as relay location and unequal power budgets at a source and a relay, are further discussed.

Secrecy Rates and Optimal Power Allocation for Full-Duplex Decode-and-Forward Relay Wire-Tap Channels

This paper investigates the secrecy rates and optimal power allocation schemes for a decode-and-forward wiretap relay channel where the transmission from a source to a destination is aided by a relay operating in a full-duplex (FD) mode under practical residual self-interference. By first considering static channels, we address the non-convex optimal power allocation problems between the source and relay nodes under individual and joint power constraints to establish closed-form solutions. An asymptotic analysis is then given to provide important insights on the derived power allocation solutions. Specifically, by using the method of dominant balance, it is demonstrated that full power at the relay is only optimal when the power at relay is sufficiently smaller when compared with that of the source. When the power at the relay is larger than the power at the source, the power consumed at the relay saturates to a constant for an effective control of self-interference. The analysis is also helpful to demonstrate that the secrecy capacity of the FD system is twice as much as that of the half-duplex system. The extension to fast fading channels with channel state information being available at the receivers but not the transmitters is also studied. To this end, we first establish a closed-form expression of the ergodic secrecy rate using simple exponential integrals for a given power allocation scheme. The results also show that with optimal power allocation schemes, FD can significantly improve the secrecy rate in fast fading environments.