Dynamic Interference Steering in Heterogeneous Cellular Networks

Li, Z.; Guo, Fengjuan; Shu, Chenchen; Shin, Kang G.; Liu, J.

doi:10.1109/access.2018.2836221

Cited by 11 publications

(8 citation statements)

References 22 publications

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“…(18), as shown at the bottom of the next page. (16) Then, the precoding vector for the steering signal can be computed as: (19) where…”

Section: B Design Of Spais With Multiple Desired and Interfering Sigmentioning

confidence: 99%

“…Note, however, the power efficiency of IS (SE at unit transmit power) is still not optimal. In order to optimally balance the transmit power for IS and desired signal's transmission, [16] proposed dynamic interference steering (DIS). Similarly to DIN, DIS can maximize the signal-to-interference-plus-noise ratio (SINR) of the interfered Rx under certain power constraint, hence optimizing the interfered transmission-pair's SE.…”

Section: Introductionmentioning

confidence: 99%

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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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“…(18), as shown at the bottom of the next page. (16) Then, the precoding vector for the steering signal can be computed as: (19) where…”

Section: B Design Of Spais With Multiple Desired and Interfering Sigmentioning

confidence: 99%

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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“…The existing IM methods can be grouped in two types. The first type is featured as the interfered receiver (Rx) or/and its associated transmitter (Tx) side implementation, including zeroforcing (ZF) reception, interference neutralization (IN) [10], [11], interference steering (IS) [12], etc. The second type is characterized by the interfering Tx side implementation, such as zero-forcing beamforming (ZFBF) [13] and interference alignment (IA) 1 [16]- [22].…”

Section: Introductionmentioning

confidence: 99%

“…Of these methods, IN and IS have been under development in recent years [10]- [12]. IN strives to properly combine signals arriving through various paths in such a way that the interfering signals are canceled while the desired signals are preserved at the Rx [10], [11]. Although IN can mitigate interference, the power overhead of generating neutralizing signal(s) degrades the system performance as well [11].…”

Section: Introductionmentioning

confidence: 99%

“…IN strives to properly combine signals arriving through various paths in such a way that the interfering signals are canceled while the desired signals are preserved at the Rx [10], [11]. Although IN can mitigate interference, the power overhead of generating neutralizing signal(s) degrades the system performance as well [11]. Under IS, a steering signal is generated to modify the propagation of interference, so that the original interference is steered in the orthogonal direction of the desired transmission at the interfered Rx.…”

Section: Introductionmentioning

confidence: 99%

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Inside-Out Precoding to Manage Multiple Interferences From the Same Source

Bai

Shin

et al. 2020

IEEE Trans. Veh. Technol.

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With the continually increasing demand for higher data rate and link density as well as better network coverage, wireless networks, including 5G-enabled vehicular communication network (VCN), will be designed/deployed to cover more overlapping areas, experiencing more severe interferences. As a result, interference becomes a key impediment to the improvement of network performance, thus requiring a thorough investigation. There have been numerous interference management (IM) methods, of which interference alignment (IA) has been receiving significant attention in recent years. IA compresses the dimension of interference subspace by confining multiple interfering signals into a finite subspace, so that the desired signal subspace may be maximized. However, when IA is applied to the situation where multiple interferences are from the same source, the interference subspace cannot be compressed due to the fact that if these interfering components are aligned in the same direction at their unintended receiver (Rx), they will become indistinguishable at their desired Rx. To solve this problem, we propose Inside-Out Precoding (IOP). With IOP, multiple data streams that may cause interference to the other Rx are at first pre-processed at the interfering transmitter (Tx), by employing an inner-precoder which makes the streams spatially separable, and then, by exploiting interactions among wireless signals, multiple interfering components are treated as an effective interference to which an outer-precoder is applied, so that multiple interferences can be compressed into one dimension at the interfered Rx while making them distinguishable at their desired Rx. We present two IOP realizations -forward IOP (F-IOP) and backward IOP (B-IOP) -and propose a protocol to realize the synchronization of processing parameters at the interfering Tx and its intended Rx so that the Rx can adapt itself to the precoding strategy employed at the Tx side. Our in-depth analysis and simulation results have shown that the proposed IOP can effectively manage multiple interferences from the same source while guaranteeing the performance of transmission from the interfering Tx to its intended Rx.

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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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Dynamic Interference Steering in Heterogeneous Cellular Networks

Cited by 11 publications

References 22 publications

Space-Power Adaptive Interference Steering to Manage Interference in XIC

Space-Power Adaptive Interference Steering to Manage Interference in XIC

Inside-Out Precoding to Manage Multiple Interferences From the Same Source

Interference management of cognitive IoT based on interference steering and alignment

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