Interference alignment(IA) is one of the promising measures for the multi-user network to manage interference. The rank constraints rank minimization means that interference spans the lowest dimensional subspace and t...Interference alignment(IA) is one of the promising measures for the multi-user network to manage interference. The rank constraints rank minimization means that interference spans the lowest dimensional subspace and the useful signal spans all available spatial dimensions. In order to improve the performance of two-way relay network, we can use rank constrained rank minimization(RCRM) to solve the IA problem. This paper proposes left reweighted nuclear norm minimization-γalgorithm and selective coupling reweighted nuclear norm minimization algorithm to implement interference alignment in two-way relay networks. The left reweighted nuclear norm minimization-γ algorithm is based on reweighted nuclear norm minimization algorithm and has a novel γ choosing rule. The selective coupling reweighted nuclear norm minimization algorithm weighting methods choose according to singular value of interference matrixes. Simulation results show that the proposed algorithms considerably improve the sum rate performance and achieve the higher average achievable multiplexing gain in two-way relay interference networks.展开更多
A key problem in code-division multiple access(CDMA)system is to mitigate the multiple access interference(MAI)from other users while detecting the desired user.The performance of the conventional minimum output energ...A key problem in code-division multiple access(CDMA)system is to mitigate the multiple access interference(MAI)from other users while detecting the desired user.The performance of the conventional minimum output energy(MOE)multiuser detector for CDMA system significantly degrades in the presence of signature waveform distortions induced by multipath propagation or timing asynchronism.In this paper,a robust linear programming(ROLP)algorithm for blind multiuser detection is proposed.Different from the existing MOE-based multiuser detection techniques,the proposed ROLP minimizes the l_∞-norm of the output to exploit the non-Gaussianity of the communication signals.To achieve robustness against signature waveform mismatch,the proposed method constrains the magnitude response of any signature vector within a specified uncertainty set to exceed unity.The uncertainty set is modeled as a rhombus,which differs from the spherical uncertainty region widely taken in the existing robust multiuser detectors.The resulting optimization problem is reformulated into a linear programming program and hence can be solved efficiently.The proposed ROLP is computationally simpler than its robust counterparts that requires solving a second-order cone programming.Simulation results demonstrate the superiority of the ROLP over several robust detectors,which indicate that its performance approaches the optimal performance bound.展开更多
Symbiotic radio(SR)is a technology that facilitates mutually beneficial sharing of spectrum and energy between primary and secondary systems.In SR networks,utilizing active reconfigurable intelligent surface(RIS)as th...Symbiotic radio(SR)is a technology that facilitates mutually beneficial sharing of spectrum and energy between primary and secondary systems.In SR networks,utilizing active reconfigurable intelligent surface(RIS)as the secondary transmitter(STx)enhances this mutual benefit compared to passive RIS.This paper addresses the interference management challenges that inevitably arise from employing active RIS.We consider a common SR network consisting of three types of users:SR users,non-SR users,and eavesdroppers.Additionally,each SR user has their own unique cellular services.We propose minimizing the total power consumption while satisfying a suffi-ciently large signal-to-interference-plus-noise ratio(SINR)for SR users,a small enough SINR for eavesdroppers,and a small enough interference temperature for non-SR users.The alternative optimization(AO)method is used for decoupling multi-variables.The non-convex constraints are relaxed as convex ones through first-order Taylor approximation,and the bounded channel state information(CSI)error model is handled using the S-procedure.Simulations validate the supe-riority of the proposed algorithm and demonstrate that the total power consumption is minimized while meeting performance thresholds.Additionally,the results offer valuable insights for SR network deployment.展开更多
基金supported by the National Science Foundation of China (NO.61271240, 61671253)
文摘Interference alignment(IA) is one of the promising measures for the multi-user network to manage interference. The rank constraints rank minimization means that interference spans the lowest dimensional subspace and the useful signal spans all available spatial dimensions. In order to improve the performance of two-way relay network, we can use rank constrained rank minimization(RCRM) to solve the IA problem. This paper proposes left reweighted nuclear norm minimization-γalgorithm and selective coupling reweighted nuclear norm minimization algorithm to implement interference alignment in two-way relay networks. The left reweighted nuclear norm minimization-γ algorithm is based on reweighted nuclear norm minimization algorithm and has a novel γ choosing rule. The selective coupling reweighted nuclear norm minimization algorithm weighting methods choose according to singular value of interference matrixes. Simulation results show that the proposed algorithms considerably improve the sum rate performance and achieve the higher average achievable multiplexing gain in two-way relay interference networks.
基金supported by the National Natural Science Foundation of China under(Grants No.62022054 and 61971279).
文摘A key problem in code-division multiple access(CDMA)system is to mitigate the multiple access interference(MAI)from other users while detecting the desired user.The performance of the conventional minimum output energy(MOE)multiuser detector for CDMA system significantly degrades in the presence of signature waveform distortions induced by multipath propagation or timing asynchronism.In this paper,a robust linear programming(ROLP)algorithm for blind multiuser detection is proposed.Different from the existing MOE-based multiuser detection techniques,the proposed ROLP minimizes the l_∞-norm of the output to exploit the non-Gaussianity of the communication signals.To achieve robustness against signature waveform mismatch,the proposed method constrains the magnitude response of any signature vector within a specified uncertainty set to exceed unity.The uncertainty set is modeled as a rhombus,which differs from the spherical uncertainty region widely taken in the existing robust multiuser detectors.The resulting optimization problem is reformulated into a linear programming program and hence can be solved efficiently.The proposed ROLP is computationally simpler than its robust counterparts that requires solving a second-order cone programming.Simulation results demonstrate the superiority of the ROLP over several robust detectors,which indicate that its performance approaches the optimal performance bound.
基金supported in part by the National Key R&D Program of China(2021YFA0716500)and in part by the National 111 Project of China(B08038).
文摘Symbiotic radio(SR)is a technology that facilitates mutually beneficial sharing of spectrum and energy between primary and secondary systems.In SR networks,utilizing active reconfigurable intelligent surface(RIS)as the secondary transmitter(STx)enhances this mutual benefit compared to passive RIS.This paper addresses the interference management challenges that inevitably arise from employing active RIS.We consider a common SR network consisting of three types of users:SR users,non-SR users,and eavesdroppers.Additionally,each SR user has their own unique cellular services.We propose minimizing the total power consumption while satisfying a suffi-ciently large signal-to-interference-plus-noise ratio(SINR)for SR users,a small enough SINR for eavesdroppers,and a small enough interference temperature for non-SR users.The alternative optimization(AO)method is used for decoupling multi-variables.The non-convex constraints are relaxed as convex ones through first-order Taylor approximation,and the bounded channel state information(CSI)error model is handled using the S-procedure.Simulations validate the supe-riority of the proposed algorithm and demonstrate that the total power consumption is minimized while meeting performance thresholds.Additionally,the results offer valuable insights for SR network deployment.
