Internet of Things (IoT) is a new paradigm that involves the interconnection of thousands of devices and home appliances. Due to the scarcity of the spectrum suitable for wireless electromagnetic transmission, many communication systems and devices are close to each other, or even overlapping in spectrum, thus incurring complicated interference situations. Therefore, interference in IoT is worthy of thorough investigation and should be well addressed. There have been numerous interference management (IM) proposals at the interfering transmitter or the interfered 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 interfered 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 with respect to 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 interfered receiver is orthogonal to its intended signal. We then apply IS to a wireless local area network (WLAN)-based IoT in which the same frequency band is reused by adjacent basic service sets (BSSs) with overlapping areas. With IS, multiple nearby access points (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.

Interference Steering to Manage Interference in IoT

In space-air-ground integrated networks (SAGIN), receivers experience diverse interference from both the satellite and terrestrial transmitters. The heterogeneous structure of SAGIN poses challenges for traditional interference management (IM) schemes to effectively mitigate interference. To address this, a novel UAV-RIS-aided IM scheme is proposed for SAGIN, where different types of channel state information (CSI) including no CSI, instantaneous CSI, and delayed CSI, are considered. According to the types of CSI, interference alignment, beamforming, and space-time precoding are designed at the satellite and terrestrial transmitter side, and meanwhile, the UAV-RIS is introduced for cooperating interference elimination process. Additionally, the degrees of freedom (DoF) obtained by the proposed IM scheme are discussed in depth when the number of antennas on the satellite side is insufficient. Simulation results show that the proposed IM scheme improves the system capacity in different CSI scenarios, and the performance is better than the existing IM benchmarks without UAV-RIS.

pdf/uav-ris-aided-space-air-ground-integrated-network-1f7377e2gt.pdf

UAV-RIS-Aided Space-Air-Ground Integrated Network: Interference Alignment Design and DoF Analysis

Heterogeneous networks (HetNets) are considered as typical application scenarios in the beyond 5th generation (B5G) and the 6th generation (6G) networks. The conventional on-ground base station (BS) has heavy traffic burden for seamless coverage and user equipments (UEs) suffer severe interference. To address these challenges, we propose a heterogeneous cloud radio access network (H-CRAN) architecture assisted by multiple unmanned aerial vehicles (UAVs). Specifically, multiple UAVs serve as flying remote radio heads (RRHs), collaborating with the macro base station (MBS), while the baseband units (BBUs) in the cloud handle processing and computing tasks. Firstly, we explore the optimal sector division scheme for the MBS and the corresponding UAV deployment scheme, considering factors like the UAV working efficiency and the overhead of interference management (IM). Despite leveraging UAVs to enhance services and offload traffic from the MBS, the proposed network inevitably encounters various categories of interference, i.e., backhaul interference, co-channel interference and multi-tier interference. To mitigate these issues, the cloud radio access networks (C-RANs) technique is employed for solving the backhaul interference. In addition, effective spatial multiplexing measures, namely sector division and beamforming are adopted by the MBS and UAV respectively to suppress the co-channel interference. We further design SIC-STIA-IS scheme, incorporating successive interference cancellation (SIC), space-time interference alignment (STIA) and interference steering (IS) scheme, to manage the cross-tier interference (CTI), intra-tier interference (ITI) and inter-cell interference (ICI), respectively. The in-depth simulation and numerical results verify that by adopting SIC-STIA-IS scheme, the proposed UAV-assisted H-CRAN architecture has superb performance in the spectral efficiency (SE).

UAV-Assisted Heterogeneous Cloud Radio Access Network With Comprehensive Interference Management

With the rapid development of wireless technologies, interference has become a main impediment to network performance, making interference management (IM) a critical issue that warrants a thorough investigation. In this paper, we propose a novel IM technique, called signal dodging and interference guiding (SDIG). With this method, we first intellectually move the data transmission away from the interference, hence can partially avoid the influence of disturbance to the desired signal. Then, we employ existing IM method, including zero-forcing (ZF) reception, interference alignment (IA), interference steering (IS), and etc., to further eliminate the interference. The SDIG consists of two phases, the first one is modifying the desired signal while the second is mitigating the interference. This is similar to the idea of Taichi in that both involve the actions of passive defense and active attack. Therefore, we also use the term Taichi as an equivalent for SDIG. Our in-depth simulation has shown that with the proposed scheme, both the interfered user's and the system's spectral efficiency can be significantly improved.

Taichi: Signal Dodging and Interference Guiding

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.

/pdf/space-power-adaptive-interference-steering-to-manage-mudp2kdotr.pdf

Space-Power Adaptive Interference Steering to Manage Interference in XIC

With the rapid development in wireless communication technologies, interference has become a main impediment to network performance, making interference management (IM) a critical issue. Interference steering (IS) is emerging as a novel way of IM, which can steer the spatial feature of interference to a target subspace by exploiting the interactions of multiple signals over the air to avoid the disturbance to the interfered receiver. In reality, there always exists multiple interferences from single or multiple sources. We propose three ways to realize IS. The first two of them are categorized as individual interference steering (IIS), in which multiple interfering signals are separately adjusted to either an identical direction ( a single-target IS , STIS) or different directions ( multi-target IS , MTIS), incurring single or multiple degrees of freedom (DoFs) overheads, respectively. Furthermore, by recognizing that the goal of IM is to limit the effect of interference—i.e., the effective portion of interference imposed on the intended transmission— we propose aggregated interference steering (AIS) that exploits the constructive or destructive effects of multiple interfering signals. By considering the overall effect of multiple interferences, the DoF cost of AIS is reduced to one regardless of the number of interference to be managed. Finally, the proposed three IS realizations are adapted to minimize the power cost of steering interference. Our theoretical analysis and in-depth simulation results have shown that the proposed IS schemes can effectively manage multiple interference via better utilizing the DoF and transmit power. The AIS is shown to be advantageous in both power cost and DoF consumption.

Design and Adaptation of Multi-Interference Steering

Interference management (IM) is essential to wireless communication systems, but it is also known to consume transmission resource such as power and degree of freedom, hence degrading users’ achievable spectral efficiency (SE) Therefore, it is important to select an appropriate IM method with optimal operating parameters so as to balance the benefits brought by and the cost of IM Interference neutralization (IN) has recently been receiving considerable attention, with which a duplicate of interference of the same strength and opposite phase with respect to the original interfering signal is generated to neutralize the disturbance at the intended receiver However, to the best of our knowledge, all existing IN schemes assume that interference is completely neutralized without accounting for their power consumption To remedy this deficiency, we propose a novel scheme, called dynamic interference neutralization (DIN) By intelligently determining the appropriate portion of interference to be neutralized, we balance the transmitter’s power used for IN and the desired signal’s transmission We then extend the proposed DIN to general cases where the numbers of interferences, desired data streams, as well as pico base stations and pico user equipments, are variables Moreover, in addition to the design under asymmetric interference topology, the application of DIN in symmetric interference situation is also presented Our in-depth analysis and simulation have shown that the proposed strategy can make better use of the transmit power than existing IM methods, hence enhancing users’ SE

When and how much to neutralize interference? Balancing the benefits and cost of interference management

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 transmission-pair’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 space-power 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 performance of the interfering transmission-pair.

/pdf/exploiting-interactions-of-multiple-interference-for-3i470zr256.pdf

Exploiting Interactions of Multiple Interference for Cooperative Interference Alignment

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Design and Adaptation of Multi-Interference Steering

When and how much to neutralize interference? Balancing the benefits and cost of interference management

Exploiting Interactions of Multiple Interference for Cooperative Interference Alignment