Decoding interfering signals with fewer receiving antennas

Li, Zhao; Dai, Xiaoqin; Shin, Kang G.

doi:10.1109/infocom.2016.7524403

Cited by 8 publications

(2 citation statements)

References 18 publications

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“…When a victim Rx suffers from multiple interferers, its associated AP asks the WLAN controller for assistance. The latter is able to check these interference components, combine them together, and then calculate an IS solution in terms of this combined interference [21]. In other words, multiple independent interferences are not treated individually but as a whole (after combining them), and hence the dimension of interference is reduced to 1.…”

Section: Multi-interference Processingmentioning

confidence: 99%

Interference Steering to Manage Interference in IoT

Liu

Shin

et al. 2019

IEEE Internet Things J.

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To enable densely deployed base stations (BSs) or access points (APs) to serve an increasing number of users and provide diverse mobile services, we need to improve spectrum utilization in wireless communication networks. Although spectral efficiency (SE) can be enhanced via smart and dynamic resource allocation, interference has become a major impediment in improving SE. There have been numerous interference management (IM) proposals at the interfering transmitter or the victim transmitter/receiver separately or cooperatively. Moreover, the existing IM schemes rely mainly on the use of channel state information (CSI). However, in some communication scenarios, the option to adjust the interferer is not available, and, in the case of downlink transmission, it is always difficult or even impossible for the victim receiver to acquire necessary information for IM.Based on the above observations, we first propose a novel IM technique, called interference steering (IS). By making use of both CSI w.r.t. and data carried in the interfering signal, IS generates a signal to modify the spatial feature of the original interference, so that the steered interference at the victim receiver is orthogonal to its intended signal. We then apply IS to an infrastructurebased enterprise wireless local area network (WLAN) in which the same frequency band is reused by adjacent basic service sets (BSSs) with overlapping areas. With IS, multiple nearby APs could simultaneously transmit data on the same channel to their mobile stations (STAs), thus enhancing spectrum reuse. Our in-depth simulation results show that IS significantly improves network SE over existing IM schemes.

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Section: Multi-interference Processingmentioning

confidence: 99%

Interference Steering to Manage Interference in IoT

Liu

Shin

et al. 2019

IEEE Internet Things J.

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“…However, SIC has an error propagation problem [9] which incurs a high bit-error rate (BER) of the subsequently decoded user data, thus limiting its application. By noting that increasing the number of receiving antennas can strengthen Rx's spatial signal processing capability, and the data carried in multiple concurrent signals can be distinguished and recovered in the spatial domain [10], some researchers incorporate multiantenna with SIC to balance the complexity and BER performance of communication systems [11,12]. However, due to equipment constraints such as hardware size and complexity, it is impractical to increase the number of receiving antennas without limit, especially for mobile devices.…”

Section: Introductionmentioning

confidence: 99%

Differentiated Reception Modes Based Multiple Access

Chang

Lyu

Peng

2022

Wireless Communications and Mobile Computing

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In recent years, the continuous increase in wireless data services and users’ traffic demand has been imposing great challenges on traditional multiple access control (MAC) methods. Some existing MAC techniques improve the communication system’s spectral efficiency (SE) via signal processing based cochannel interference (CCI) management. However, no interference management (IM) is free, i.e., its realization is based on the consumption of some communication resources, such as power and degree-of-freedom (DoF), which can also be used for the user’s desired data transmission. To lessen the resource cost for IM-based MAC, we exploit interactions among multiple wireless signals to propose a new MAC method, namely, Differentiated Reception Modes based Multiple Access (DRM-MA), in this paper. Under DRM-MA, a central control unit (CCU) is adopted to manage and pair multiple transmitting antennas with their serving receivers (Rxs). The CCU first calculates the phase difference of signals sent from each candidate antenna and perceived by the two receiving antennas of an Rx based on the locations of the transmitting antenna and Rx. Then, the CCU selects and pairs a proper transmitting antenna with each Rx, so that various Rxs can adopt either additive or subtractive reception mode to postprocess the signals received by its two antennas to realize in-phase desired signal construction and inverse-phase interference destruction. DRM-MA can avoid transmission performance loss incurred by signal processing-based IM. Our theoretical analysis and simulation results have shown that DRM-MA can enable concurrent data transmissions of multiple antenna-receiver pairs and output a high system’s SE.

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