In-band full duplex wireless is of utmost interest to future wireless communication and networking due to great potentials of spectrum efficiency. IBFD wireless, however, is throttled by its key challenge, namely self-interference. Therefore, effective self-interference cancellation is the key to enable IBFD wireless. This paper proposes a real-time non-linear self-interference cancellation solution based on deep learning. In this solution, a self-interference channel is modeled by a deep neural network (DNN). Synchronized self-interference channel data is first collected to train the DNN of the self-interference channel. Afterwards, the trained DNN is used to cancel the self-interference at a wireless node. This solution has been implemented on a USRP SDR testbed and evaluated in real world in multiple scenarios with various modulations in transmitting information including numbers, texts as well as images. It results in the performance of 17dB in digital cancellation, which is very close to the self-interference power and nearly cancels the self-interference at a SDR node in the testbed. The solution yields an average of 8.5 bit error rate (BER) over many scenarios and different modulation schemes.
As far as the performance of IBFD wireless solutions is concerned, some works have reported that the channel capacity could be doubled on a single-hop link, while in mesh network the actual benefit of IBFD wireless may be effected by spatial reuse and asynchronous contention @cite_6 . Another works @cite_2 @cite_13 shows 1.87 times throughput improvement and 1.42 times capacity over a half-duplex system at a transmission power of 20 dBm. A recent work @cite_0 shows that at a certain situation, IBFD wireless can double the downlink and uplink throughputs of static TDD. Another recent work reported a performance improvement by 30
@cite_0 @cite_13 @cite_6 @cite_2
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In-band full duplex has emerged as a solution for high data rate and low access delay for 5G wireless networks after its feasibility has been demonstrated. However, the impact of the in-band full duplex on the system-level performance of multi-cell wireless networks has not been investigated thoroughly. In this paper, we conduct an extensive simulation study to investigate the performance of in-band full duplex for indoor 5G small cell wireless networks. Particularly, we compare the in-band full duplex with static and dynamic time division duplexing schemes which require much less hardware complexity. We examine the effects of beamforming and interference cancellation under various traffic demands and asymmetry situations in the performance comparison. Our objective is to identify under which condition and with which technology support the in-band full duplex becomes advantageous over the simpler duplexing schemes. Numerical results indicate that for highly utilized wireless networks, in-band full duplex should be combined with interference cancellation and beamforming in order to achieve a performance gain over traditional duplexing schemes. Only then in-band full duplex is considered to be advantageous at any number of active mobile stations in the network and any downlink to uplink traffic proportion. Our results also suggest that in order to achieve a performance gain with the in-band full duplex in both links, the transmit power of the access points and the mobile stations should be comparable. Half duplex radios use two separate frequency bands to enable simultaneous transmission and reception. Recently, full duplex radio that allows a wireless node to transmit and receive simultaneously in one frequency band was proposed. We propose a MAC protocol for full duplex radio networks, FDMAC, which is a simple and efficient protocol compatible with IEEE 802.11 MAC protocol. We analyze the performance of full duplex wireless networks with FD-MAC considering both the physical layer and the MAC layer. This paper presents the design and implementation of the first in-band full duplex WiFi radios that can simultaneously transmit and receive on the same channel using standard WiFi 802.11ac PHYs and achieves close to the theoretical doubling of throughput in all practical deployment scenarios. Our design uses a single antenna for simultaneous TX RX (i.e., the same resources as a standard half duplex system). We also propose novel analog and digital cancellation techniques that cancel the self interference to the receiver noise floor, and therefore ensure that there is no degradation to the received signal. We prototype our design by building our own analog circuit boards and integrating them with a fully WiFi-PHY compatible software radio implementation. We show experimentally that our design works robustly in noisy indoor environments, and provides close to the expected theoretical doubling of throughput in practice.