Design and Adaptation of Multi-Interference Steering

Li, Zhao; Liu, Yinghou; Shin, Kang G.; Li, Jun; Guo, Fengjuan; Liu, Jia

doi:10.1109/twc.2019.2908158

Cited by 12 publications

(11 citation statements)

References 38 publications

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“…There have been various interference management schemes that can be categorized in two types. The first type is realized at the interfered transmission-pair, including the adjustment at the interfered receiver or/and its associated transmitter, e.g., zero-forcing reception [3], interference neutralization [4,5], and interference steering [6,7]. The second type is realized at the interfering transmitter, such as zero-forcing beamforming [8] and interference alignment (IA) 1 [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

“…Under interference steering, a steering signal is generated to modify the propagation of interfering signal, so that the original interference is steered in the orthogonal direction of the desired transmission at the interfered receiver. In contrast with interference neutralization, interference steering focuses on the cancellation of the effective part of interference, thus becoming more power-efficient [6,7], but requires an additional spatial DoF to place the steered interference. The authors of [7] proposed single-target interference steering and aggregated interference steering to manage multiple interferences.…”

Section: Introductionmentioning

confidence: 99%

“…Based on the above discussion, effective management of multiple interferences from the same source with little or no transmitter-side cooperation overhead [11][12][13][14][15][16][17][18][19], transmit power consumption [4][5][6][7]19] at the interfered transmitter, interfered receiver-side DoF cost, as well as performance loss of interfering transmission-pair, is of great importance to emerging ultra-dense wireless networks. To meet this need, we propose a novel interference management method called cooperative interference alignment (i.e., cooperative IA).…”

Section: Introductionmentioning

confidence: 99%

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Exploiting Interactions of Multiple Interference for Cooperative Interference Alignment

Liu

et al. 2021

IEEE Trans. Wireless Commun.

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Wireless networks are usually deployed to cover more overlapping areas, experiencing severe interferences and hence making interference management essential for their viability. Interference alignment (IA) is an effective way of interference management and has thus received significant attention. With IA, at least one degree-of-freedom (DoF) should be used to place the aligned interferences. However, when multiple interferences are from one identical transmitter and to a common destination, IA is not applicable under a one-DoF cost constraint. If these interfering signals are aligned in the same direction at the interfered receiver, they will also overlap with each other at their intended receiver, thus becoming indistinguishable. Moreover, IA is realized by adjusting the spatial feature of disturbance, hence incurring co-channel interference to the interfering transmissionpair's own communication. To solve this problem, we propose cooperative IA. Instead of adjusting the spatial characteristics of all interferences, we aim to achieve IA by adjusting interferences' strength along with one or none interference's signature, based on the interactions among multiple wireless disturbances. We propose two cooperative IA schemes: cooperative IA with spacepower adjustment and cooperative IA with power adjustment. With the first method, the overall effect of all interferences is aligned in the orthogonal direction with respect to the desired signal at the interfered receiver. This method modifies the direction of one interference with a properly designed precoding vector and the strength of all interferences via power allocation. Under the second scheme, the strength of all interfering signals is modified so that the overall effect of multiple interferences is orthogonal to the desired transmission while guaranteeing the orthogonality among the interfering signals at their intended receiver. Our theoretical analysis and in-depth simulation have shown that the proposed schemes can effectively manage multiple interferences from an identical source while achieving good

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Exploiting Interactions of Multiple Interference for Cooperative Interference Alignment

Liu

et al. 2021

IEEE Trans. Wireless Commun.

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“…In order to manage interference in various communication scenarios, a variety of IM methods, such as zero-forcing beamforming (ZFBF) [11], interference cancellation (IC) [12], interference alignment (IA) [13], interference neutralization (IN) [14], and interference steering (IS) [15]- [17], have been proposed. The authors of [11] proposed a ZFBF scheme for multiple-input multiple-output (MIMO) broadcast channel.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, researchers continually design new IM methods, e.g. IN [14] and IS [15]- [17]. IN seeks to properly combine signals arriving from various paths in such a way that the interfering signals are canceled while the desired signals are preserved [14].…”

Section: Introductionmentioning

confidence: 99%

Space-Power Adaptive Interference Steering to Manage Interference in XIC

Liu

Ding

et al. 2020

IEEE Access

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With the rapid development of wireless communication technologies, interference has become a key impediment in the improvement of network capacity. In practice, although dense deployment of network can effectively increase the spectrum efficiency, severe co-channel interference (CCI) is likely incurred, especially for mobile users in the overlapping areas of multiple access points, leading to serious deterioration of these users' spectral efficiency (SE). Interference steering (IS), emerging as a novel interference management (IM) scheme, can not only eliminate the impact of interference on the desired transmission, but also incur less power overhead than other IM methods. Although some works conducted flexible design of IS via power domain adaptation, the space domain flexibility has not been exploited. Moreover, existing IS works are mainly for the Z-interference channel (ZIC), while in practical use X-interference channel (XIC) is more common. To remedy the above deficiencies, this paper proposes a space-power adaptive interference steering (SPAIS) method in XIC. By adaptively adjusting the strength and spatial feature of the steering signal, SPAIS can not only effectively suppress interference imposed on the interfered receiver (Rx), but also make full use of the power of the steering signal, thus enhancing desired data transmission. Our in-depth simulation results show that compared to existing IM methods, SPAIS can significantly improve the users' SE performance.

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Interference management of cognitive IoT based on interference steering and alignment

Sun,

Qian,

Liu

et al. 2024

Trans Emerging Tel Tech

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In the cognitive IoT spectrum sharing process, the complex interference environment leads to a low spectral efficiency of the licensed spectrum. To solve this problem, this article allows more cognitive users (CU) to access the licensed spectrum while ensuring reliable transmission of primary users (PU) by introducing the advanced interference steering (IS) technique. Traditional IS methods are only suitable for single‐user and single‐data‐stream scenarios. Meanwhile, these methods have many drawbacks in multi‐user and multi‐data‐stream scenarios. To overcome these drawbacks, two IS algorithms based on time division (TD) multiple access are proposed in this article, which are TD based equivalent interference sub‐channel interference steering (TD‐EI‐SCIS) and TD‐based sub‐channel interference steering (TD‐SCIS), respectively. Furthermore, considering the fact that PU has the highest communication quality priority in cognitive IoT, a joint interference management (JIM) scheme based on TD‐EI‐SCIS, TD‐SCIS, and partial interference alignment (PIA) is proposed to protect the PU. Simulation results show that the spectral efficiency (SE) of the PU in the proposed JIM scheme is not significantly improved compared with the proposed TD‐EI‐SCIS in the low SNR region. However, from the perspective of the total SE in the whole cognitive IoT system, TD‐EI‐SCIS is superior to the JIM about 3 to 4 bit/s/Hz on average. In the high SNR region, the JIM scheme significantly outperforms TD‐EI‐SCIS not only in terms of the SE of PU about 10 bit/s/Hz but also in the aspect of the SE in the total network about 7 bit/s/Hz on average.

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Design and Adaptation of Multi-Interference Steering

Cited by 12 publications

References 38 publications

Exploiting Interactions of Multiple Interference for Cooperative Interference Alignment

Exploiting Interactions of Multiple Interference for Cooperative Interference Alignment

Space-Power Adaptive Interference Steering to Manage Interference in XIC

Interference management of cognitive IoT based on interference steering and alignment

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