In this paper, multiple device-to-device (D2D) communication underlaying cellular multiuser multiple inputs multiple outputs (MU-MIMO) systems is investigated. This type of communication can improve spectral efficiency to address future demand, but interference management, user clustering, and resource allocation are three key problems related to resource sharing. Interference alignment (IA) is proposed to better mitigate in-cluster interference compared with a multiplex scheme, and user clustering and resource allocation are jointly investigated using binary-integer programming. In addition to an exhaustive search for a maximum throughput, we propose a two-step suboptimal algorithm by reducing the search space and applying branch-and-bound searching (BBS). To further obtain a good trade-off between performance and complexity, we propose a novel algorithm based on distance-constrained criteria for user clustering. The simulation results show that the IA and multiplex schemes acquiring user clustering gains outperform the orthogonal scheme without user clustering. Besides, the proposed two-step and location-based algorithms achieve little losses compared with the optimal algorithm under low complexities.
It is well known that relay is able to neutralize some interferences in destinations. In this paper we use not only relay to neutralize interferences but also interference alignment to reduce the number of antennas needed in destinations. To this end, a scheme of cognitive relay-aided interference neutralization and alignment is proposed. To neutralize and align interferences, the relay needs to retransmit the signals using proper transmitting vectors. We demonstrate that the 3-user MIMO interference channels with cognitive relay can achieve 2M degrees of freedom (DoF) when each node has M antennas. It is a big improvement compared to k-user system using interference alignment which is able to obtain 3M/2 DoF. The transmitting vectors in sources and relay are carefully designed to not only satisfy the neutralization and alignment constraints but also achieve higher sum-rate, which can be proved by simulation results.Index Terms-Interference Alignment(IA), Interference Neutralization(IN), Cognitive Relay(CR), multiple-in multiple-out (MIMO), sum-rate, degrees of freedom(DoF).
Spread spectrum communication is a typical scheme for covert communication because of its low detectability and antijam characteristic. However, the associated design concerns multiple factors, such as cochannel multiple access interference (MAI) and spread spectrum gain. In this paper, the lattice reduction theory is applied to MAI cancellation of spread spectrum communication and a novel lattice reduction aided multiple user detection method is proposed. The near maximum likelihood (ML) performance of MAI resistance is verified by simulation and theoretical analysis. The superiority of detection performance in strong MAI scenarios is especially addressed. Based on the algorithm, a collaborative covert communication system design is proposed. Low-power covert signals can be transmitted at a higher bit rate with the same coverage as more high-power cochannel signals. The covert transmission performance can be improved significantly compared to traditional designs.
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