Transmission Capacity of Full-Duplex MIMO Ad-Hoc Network with Limited Self-Interference Cancellation

In this paper, we propose a joint transceiver beamforming design to simultaneously mitigate self-interference (SI) and partial inter-node interference for full-duplex multiple-input and multiple-output ad-hoc network, and then derive the transmission capacity upper bound (TC-UB) for the corresponding network. Condition on a specified transceiver antenna's configuration, we allow the SI effect to be cancelled at transmitter side, and offer an additional degree-of-freedom at receiver side for more inter-node interference cancellation. In addition, due to the proposed beamforming design and imperfect SI channel estimation, the conventional method to obtain the TC-UB is not applicable. This motivates us to exploit the dominating interferer region plus Newton-Raphson method to iteratively formulate the TC-UB. The results show that the derived TC-UB is quite close to the actual one especially when the number of receive-antenna is small. Moreover, our proposed beamforming design outperforms the existing beamforming strategies, and FD mode works better than HD mode in low signal-to-noise ratio region.Comment: 7 pages, 4 figures, accepted by Globecom 201

Multi-Antenna Assisted Virtual Full-Duplex Relaying with Reliability-Aware Iterative Decoding

In this paper, a multi-antenna assisted virtual full-duplex (FD) relaying with reliability-aware iterative decoding at destination node is proposed to improve system spectral efficiency and reliability. This scheme enables two half-duplex relay nodes, mimicked as FD relaying, to alternatively serve as transmitter and receiver to relay their decoded data signals regardless the decoding errors, meanwhile, cancel the inter-relay interference with QR-decomposition. Then, by deploying the reliability-aware iterative detection/decoding process, destination node can efficiently mitigate inter-frame interference and error propagation effect at the same time. Simulation results show that, without extra cost of time delay and signalling overhead, our proposed scheme outperforms the conventional selective decode-and-forward (S-DF) relaying schemes, such as cyclic redundancy check based S-DF relaying and threshold based S-DF relaying, by up to 8 dB in terms of bit-error-rate.Comment: 6 pages, 4 figures, conference paper has been submitte

Cooperative Full-Duplex Physical and MAC Layer Design in Asynchronous Cognitive Networks

In asynchronous cognitive networks (CNs), where there is no synchronization between primary users (PUs) and secondary users (SUs), spectrum sensing becomes a challenging task. By combining cooperative spectrum sensing and full-duplex (FD) communications in asynchronous CNs, this paper demonstrates improvements in terms of the average throughput of both PUs and SUs for particular transmission schemes. The average throughputs are derived for SUs and PUs under different FD schemes, levels of residual self-interference, and number of cooperative SUs. In particular, we consider two types of FD schemes, namely, FD transmit-sense-reception (FDr) and FD transmit-sense (FDs). FDr allows SUs to transmit and receive data simultaneously, whereas, in FDs, the SUs continuously sense the channel during the transmission time. This paper shows the respective trade-offs and obtains the optimal scheme based on cooperative FD spectrum sensing. In addition, SUs’ average throughput is analyzed under different primary channel utilization and multichannel sensing schemes. Finally, new FD MAC protocol design is proposed and analyzed for FD cooperative spectrum sensing. We found optimum parameters for our proposed MAC protocol to achieve higher average throughput in certain applications

Energy Efficient Resource Allocation for Mobile-Edge Computation Networks with NOMA

This paper investigates an uplink non-orthogonal multiple access (NOMA)-based mobile-edge computing (MEC) network. Our objective is to minimize the total energy consumption of all users including transmission energy and local computation energy subject to computation latency and cloud computation capacity constraints. We first prove that the total energy minimization problem is a convex problem, and it is optimal to transmit with maximal time. Then, we accordingly proposed an iterative algorithm with low complexity, where closed-form solutions are obtained in each step. The proposed algorithm is successfully shown to be globally optimal. Numerical results show that the proposed algorithm achieves better performance than the conventional methods.Comment: 7 pages 5 figures. arXiv admin note: text overlap with arXiv:1807.1184