Rate-Energy Balanced Precoding Design for SWIPT based Two-Way Relay Systems
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Simultaneous wireless information and power transfer (SWIPT) technique is a popular strategy to convey both information and RF energy for harvesting at receivers. In this regard, we consider a relay employing SWIPT strategy, where splitting the received signal leads to a rate-energy trade-off. In literature, the works on transceiver design have been studied using computationally intensive and suboptimal convex relaxation based schemes. In this paper, we study the balanced precoder design using chordal distance (CD) decomposition to provide a better rate-energy trade-off, which incurs much lower complexity and flexible to dynamic energy requirements. It is analyzed that given a non-negative value of CD, the achieved harvested energy for the proposed balanced precoder is higher than that for the perfect interference alignment (IA) precoder, while verifying the analyzed loss in sum rates. Simulation results verify the analysis and add that the IA schemes based on mean-squared error are better suited for the SWIPT maximization than the subspace alignment-based methods.Keywords:
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This paper proposes a robust transmission design for simultaneous wireless information and power transfer (SWIPT) in a multiuser multiple-input single-output (MISO) broadcast system, under the assumption of imperfect channel state information (CSI) at the transmitter. Our design objective is to maximize the minimum harvested energy of all the receivers by jointly optimizing the transmit beamforming vectors and the power splitting ratios while guaranteeing the signal-to-interference-and-noise ratio (SINR) and total transmit power constraints. The aforementioned max-min problem is non-convex due to the existing of infinite number of constraints, and thus it is difficult to solve. To tackle it, we first convert it into an easier non-convex problem with finite constraints by using some certain transformation techniques. Then, with the aid of the semidefinite relaxation (SDR) technique, we further obtain a relaxed semidefinite programming (SDP) problem, which is convex and thus can be solved efficiently by using interior point methods. Finally, simulation results are provided to validate the robustness and effectiveness of the proposed scheme.
Robustness
Semidefinite Programming
Transmitter power output
Channel state information
Interior point method
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By considering the Simultaneous Wireless Information and Power Transfer (SWIPT) schemes, this paper focuses on secure transmission model design in multiple-input-single-output (MISO) channels. In these channels, the channel state information is assumed to be perfect. Our objective is to maximize the worst-case secrecy rate with respect to both potential eavesdroppers and obvious eavesdroppers under the constraints of energy-harvesting and total transmission power. We present an optimization model to indirectly obtain maximum security rate in a single receiver system. Due to the high computational complexity of the solution process caused by the formulated non-convex optimization problem, we propose a novel indirect method to handle this issue. Then, a Semi-Definite Programming (SDP) relaxation method is used to approach the optimal solution. Moreover, we reveal the conditions for ensuring that the above semi-definite relaxation is compact. Simulation results demonstrate that the gained performance in our system is much better than those of the existing competing schemes.
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We study the beamforming design for multiuser systems with simultaneous wireless information and power transfer (SWIPT). Employing a practical non-linear energy harvesting (EH) model, the design is formulated as a non-convex optimization problem for the maximization of the minimum harvested power across several energy harvesting receivers. The proposed problem formulation takes into account imperfect channel state information (CSI) and a minimum required signal-to-interference-plus-noise ratio (SINR). The globally optimal solution of the design problem is obtained via the semidefinite programming (SDP) relaxation approach. Interestingly, we can show that at most one dedicated energy beam is needed to achieve optimality. Numerical results demonstrate that with the proposed design a significant performance gain and improved fairness can be provided to the users compared to two baseline schemes.
Semidefinite Programming
Maximization
Channel state information
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The joint design of beamforming vector and artificial noise covariance matrix is investigated for the multiple-input-single-output-multiple-eavesdropper simultaneous wireless information and power transferring \mbox{(MISOME-SWIPT)} systems. In the MISOME-SWIPT system, the base station delivers information signals to the legitimate user equipments and broadcasts jamming signals to the eavesdroppers. A secrecy energy efficiency (SEE) maximization problem is formulated for the considered \mbox{MISOME-SWIPT} system with imperfect channel state information, where the SEE is defined as the ratio of sum secrecy rate over total power consumption. Since the formulated SEE maximization problem is non-convex, it is first recast into a series of convex problems in order to obtain the optimal solution with a reasonable computational complexity. Two suboptimal solutions are also proposed based on the heuristic beamforming techniques that trade performance for computational complexity. In addition, the analysis of computational complexity is performed for the optimal and suboptimal solutions. Numerical results are used to verify the performance of proposed algorithms and to reveal practical insights.
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In this paper, the problem of mutual information maximization in a two-hop multiple-input multiple-output (MIMO) relay network with simultaneous wireless information and power transfer (SWIPT) is investigated, where the relay node, without constant power supply, harvests the energy for information forwarding. The goal is to maximize the mutual information by using the joint design of source and relay precoders, which is formulated as an optimization problem under the constraints of transmit power and harvested energy. Two scenarios with practical energy harvesting schemes employed at the relay, i.e., power splitting (PS) and time switching (TS) schemes, are considered. Although the formulated optimization problems in the two scenarios are both nondeterministic polynomial-time (NP)-hard, by exploiting the structure of the optimization problems and analyzing the characteristics of precoders, we develop near optimal joint source and relay precoding algorithms for them. Additionally, we analyze the feasible regions of PS and TS ratios, respectively, and propose a backtracking line search based method to find near optimal PS and TS ratios. The main contributions of this paper are as follows: 1) Unlike existing works based on the assumption of ideal Gaussian signals, this paper supposes the inputs to the network are finite-alphabet signals, which is a more practical scenario. 2) The high complexity of mutual information with finite-alphabet signals leads to an intractable optimization problem; however, an efficient solving framework based on semidefinite relaxation (SDR) and Karush-Kuhn-Tucker (KKT) theorem is proposed. Finally, simulation results verify the efficacy of the proposed joint precoding designs.
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Existing research on a simultaneous wireless information and power transfer (SWIPT) system is based on the assumption of Gaussian inputs. However, the optimal design on Gaussian inputs may lead to dramatic performance loss for practical systems with finite-alphabet inputs. This paper focuses on the precoder design for a SWIPT system with finite-alphabet inputs and instantaneous channel state information over a multiple-input multiple-output channel. We formulate the optimal precoder design as an optimization problem, in which the objective is to maximize the mutual information over the channel from the transmitter to the information receiver under the constraints of transmit power and harvested energy threshold. The formulated problem is NP-hard, so a global optimal solution cannot be found within the polynomial time. The main contributions of this paper are as follows: 1) By using its structure, the NP-hard problem is relaxed to a semidefinite programming problem. Then, a general solving framework for both co-located and separated receiver cases, based on the semidefinite relaxation (SDR) technique, is developed to achieve a near optimal precoder. 2) For the case of co-located receivers, we show that the optimal precoder design is a concave problem with respect to power allocation; then, a specific algorithm for co-located receivers is proposed. Compared with the general SDR-based method, the specific algorithm for co-located receivers exhibits almost the same performance but much lower complexity. 3) The performance of several practical co-located receiver designs is analyzed in SWIPT systems with finite-alphabet inputs. Finally, we provide simulation results to show the efficacy of the proposed algorithms.
Semidefinite Programming
Transmitter power output
Channel state information
Optimal design
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Energy efficiency (EE) is a key issue in energy-constrained wireless networks because of the energy scarcity. In this paper, we present the robust energy-efficient optimization design for multiple-input-multiple-output two-way relay networks with simultaneous wireless information and power transfer, where the available channel state information is considered to be imperfect. We model the channel errors by using the norm bounded model, and aim to maximize the worst-case EE by jointly designing the precoders of the sources and relay, and the power splitting ratio of the relay under the worst-case transmit power constraints at the sources and relay. To solve the robust EE optimization problem, we propose an iterative optimization algorithm based on the weighted minimum mean-square-error method, where the S-procedure and sign-definiteness lemma are employed to eliminate the channel errors. To balance the performance and complexity, we propose a channel diagonalization algorithm based on the generalized singular value decomposition, which has lower complexity. The effectiveness of the proposed algorithms is shown by numerical results.
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This paper investigates the simultaneous wireless information and power transfer (SWIPT) precoding scheme for K-user multiple-input-multiple-output (MIMO) interference channels (IC). In IC, interference alignment (IA) schemes provide optimal precoders to achieve full degrees-of-freedom (DoF) gain. To study a trade-off between harvested energy and sum rate, the transceiver design problem is suboptimally formulated in literature via convex relaxations, which is still computationally intensive, especially for battery limited nodes running on harvested energy. In this paper, we propose a systematic method using chordal distance (CD) decomposition to obtain the balanced precoding, which achieves the improved trade-off. Analysis shows that given the nonnegative value of CD, the achieved harvested energy for the proposed precoder is higher than that for perfect IA precoder. Moreover, energy constraints can be achieved, while maintaining a constant rate loss without losing DoFs via tuning the CD value and splitting factor. Simulation results verify the analysis and add that the IA schemes based on max-SINR or mean-squared error are better suited for SWIPT maximization than subspace or leakage minimization methods.
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This paper considers power splitting (PS)-based simultaneous wireless information and power transfer (SWIPT) for multiple-input multiple-output (MIMO) interference channel networks where multiple transceiver pairs share the same frequency spectrum. As the PS model is adopted, an individual receiver splits the received signal into two parts for information decoding (ID) and energy harvesting (EH), respectively. Aiming to minimize the total transmit power, transmit precoders, receive filters and PS ratios are jointly designed under a predefined signal-to-interference-plus-noise ratio (SINR) and EH constraints. The formulated joint transceiver design and power splitting problem is non-convex and thus difficult to solve directly. In order to effectively obtain its solution, the feasibility conditions of the formulated non-convex problem are first analyzed. Based on the analysis, an iterative algorithm is proposed by alternatively optimizing the transmitters together with the power splitting factors and the receivers based on semidefinite programming (SDP) relaxation. Moreover, considering the prohibitive computational cost of the SDP for practical applications, a low-complexity suboptimal scheme is proposed by separately designing interference-suppressing transceivers based on interference alignment (IA) and optimizing the transmit power allocation together with splitting factors. The transmit power allocation and receive power splitting problem is then recast as a convex optimization problem and solved efficiently. To further reduce the computational complexity, a low-complexity scheme is proposed by calculating the transmit power allocation and receive PS ratios in closed-form. Simulation results show the effectiveness of the proposed schemes in achieving SWIPT for MIMO interference channel (IC) networks.
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In this paper, we investigate a new approach for simultaneous wireless information and power transfer (SWIPT) in point-to-point multiple-input multiple-output (MIMO) system with spatial switching (SS) reception. The new approach is based on the generalized triangular decomposition (GTD). The approach takes advantage of the GTD structure to allow the transmitter to use the strongest subchannel jointly for energy harvesting and information exchange while these transmissions can be separated at the receiver to comply with the SS system requirements. An optimal solution is developed in the paper for SWIPT based on GTD that jointly obtains the optimal subchannels assignment and maximizes the total data rate while meeting the minimum requirement of the harvested energy with limited total transmitted power. The theoretical and numerical results presented in this paper show that the proposed approach significantly outperforms the state of the art spatial domain SWIPT systems based on the singular value decomposition (SVD).
Maximization
Transceiver
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