Interference Alignment in Two-Way Relay Networks via Rank Constraints Rank Minimization

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.

The Average Achievable Rate of Multi-Antenna Two-Way Relay Networks with Interference Alignment

The large system analysis(LSA)has recently been shown to be a very useful tool for computing the average achievable rate.In this paper,we use LSA to derive the users’average achievable rate of multi-antenna two-way relay networks with interference alignment(IA),and we then derive the rate expressions under both equal power allocation and optimal power allocation.It is shown that the obtained closed-form rate expressions are functions of the average signal-to-noise ratio(SNR)for each data stream.Extensive simulation studies show that the average achievable rate expressions derived through LSA provide accurate estimates of the average achievable rate for two-way relay networks with interference alignment.

Quantum Algorithm for Appointment Scheduling

Suppose a practical scene that when two or more parties want to schedule anappointment, they need to share their calendars with each other in order to make itpossible. According to the present result the whole communication cost to solve thisproblem should be their calendars’ length by using a classical algorithm. In this work, weinvestigate the appointment schedule issue made by N users and try to accomplish it inquantum information case. Our study shows that the total communication cost will bequadratic times smaller than the conventional case if we apply a quantum algorithm in theappointment-scheduling problem.

Quantum Multi-User Detection Based on Coherent State Signals

Multi-user detection is one of the important technical problems for moderncommunications. In the field of quantum communication, the multi-access channel onwhich we apply the technology of quantum information processing is still an openquestion. In this work, we investigate the multi-user detection problem based on thebinary coherent-state signals whose communication way is supposed to be seen as aquantum channel. A binary phase shift keying model of this multi-access channel isstudied and a novel method of quantum detection proposed according to the conclusionof the quantum measurement theory. As a result, the average interference betweendeferent users is presented and the average error probability of the quantum detection isderived theoretically. Finally, we show the maximum channel capacity of this effectivedetection for a two-access quantum channel.