Cross-link Interference Research Articles

Cross-link Interference Mitigation Method for Heterogeneous Frame Structures of 5G-Advanced Networ

Cross-link Interference Mitigation Method for Heterogeneous Frame Structures of 5G-Advanced Networ

Adaptive Multilink Channel Access Under Cross-Link Interference in Next-Generation WLANs

Adaptive Multilink Channel Access Under Cross-Link Interference in Next-Generation WLANs

Cross-link interference in the 5G cell search procedure: Observation and field experiments for mitigation

This paper presents field experiment results that illustrate the impact of cross-link interference on the cell search procedure in a 5G time division duplex system. We initially show how cross-link interference affects to the cell search procedure from an analytic aspect. An example of an experimental result provided in this paper shows how the user equipment wrongly estimates the symbol timing offset due to cross-link interference. Furthermore, we propose a modified cell search algorithm which is robust against the strong influence of cross-link interference. The proposed modification efficiently suppresses the effects of cross-link interference by applying selective energy normalization to the correlation process. The experimental results show that the modified algorithm can accurately estimate the symbol timing offset with a negligible increment in computation time.

Network-assisted full-duplex cell-free mmWave networks: Hybrid MIMO processing and multi-agent DRL-based power allocation

This paper investigates the network-assisted full-duplex (NAFD) cell-free millimeter-wave (mmWave) networks, where the distribution of the transmitting access points (T-APs) and receiving access points (R-APs) across distinct geographical locations mitigates cross-link interference, facilitating the attainment of a truly flexible duplex mode. To curtail deployment expenses and power consumption for mmWave band operations, each AP incorporates a hybrid digital–analog structure encompassing precoder/combiner functions. However, this incorporation introduces processing intricacies within channel estimation and precoding/combining design. In this paper, we first present a hybrid multiple-input multiple-output (MIMO) processing framework and derive explicit expressions for both uplink and downlink achievable rates. Then we formulate a power allocation problem to maximize the weighted bidirectional sum rates. To tackle this non-convex problem, we develop a collaborative multi-agent deep reinforcement learning (MADRL) algorithm called multi-agent twin delayed deep deterministic policy gradient (MATD3) for NAFD cell-free mmWave networks. Specifically, given the tightly coupled nature of both uplink and downlink power coefficients in NAFD cell-free mmWave networks, the MATD3 algorithm resolves such coupled conflicts through an interactive learning process between agents and the environment. Finally, the simulation results validate the effectiveness of the proposed channel estimation methods within our hybrid MIMO processing paradigm, and demonstrate that our MATD3 algorithm outperforms both multi-agent deep deterministic policy gradient (MADDPG) and conventional power allocation strategies.

CrossTrack: Device-Free Cross-Link Tracking With Commodity Wi-Fi

Device-free Wi-Fi tracking has become essential for ubiquitous wireless sensing. However, current device-free Wi-Fi tracking systems suffer from two limitations: First, Abnormal signals interfere with tracking performance when the user walks across the direct link of the transceivers; Second, The tracking error based on the velocity integral accumulates over time. This paper proposes CrossTrack, the first device-free cross-link tracking system with commodity Wi-Fi. Our inspiration is to regard the cross-link behavior as an opportunity to correct the trajectory instead of disturbing noise like previous work. Our approach involves three main steps. First, we devise a metric that is capable of detecting cross-link behavior. Second, we propose a new theoretical model that identifies the cross-link position as a landmark. Third, we develop a path revision technique that utilizes this landmark to optimize the trajectory. The technique innovation of the paper is to reveal the theoretical approach to transform cross-link interference into optimization in device-free tracking for the first time. We implement CrossTrack based on commercial Wi-Fi devices and conduct comprehensive experiments. Our results show that CrossTrack can reduce tracking errors by 48.75%, and the median tracking error is 0.41m.

LoneSTAR: Analog Beamforming Codebooks for Full-Duplex Millimeter Wave Systems

This work develops LONESTAR, a novel enabler of full-duplex millimeter wave (mmWave) communication systems through the design of analog beamforming codebooks. LONESTAR codebooks deliver high beamforming gain and broad coverage while simultaneously reducing the self-interference coupled by transmit and receive beams at a full-duplex mmWave transceiver. Our design framework accomplishes this by tolerating some variability in transmit and receive beamforming gain to strategically shape beams that reject self-interference spatially while accounting for digitally-controlled analog beamforming networks and self-interference channel estimation error. By leveraging the coherence time of the self-interference channel, a mmWave system can use the same LONESTAR design over many time slots to serve several downlink-uplink user pairs in a full-duplex fashion without the need for additional self-interference cancellation. Compared to those using conventional codebooks, full-duplex mmWave systems employing LONESTAR codebooks can mitigate higher levels of self-interference, tolerate more cross-link interference, and demand lower SNRs in order to outperform half-duplex operation—all while supporting beam alignment. This makes LONESTAR a potential standalone solution for enabling simultaneous transmission and reception in mmWave systems, from which it derives its name.

Design of Antenna Polarization Plane for Concurrent Uplink/Downlink Drone Networks

In recent years, drones have been used in a wide range of fields, such as agriculture, transportation of goods, and security. Drones equipped with communication facilities are expected to play an active role as base stations in areas where ground base stations are unavailable, such as disaster areas. In addition, asynchronous operation is being considered for local 5G, in order to support all kinds of use cases. In asynchronous operation, cross-link interference between base stations is an issue. This paper attempts to reduce the interference caused by the drone network by introducing circularly polarized antennas against the conventional system using linearly polarized antennas. Numerical analyses are conducted to validate the effectiveness of the proposed system, where Signal-to-Interference Ratios (SIRs) are shown to be improved significantly as the numerical evaluation results. Specifically, for the scenario of only access links, in the region where conventional antenna architecture can only achieve an SIR of less than 20 dB, our proposed system applying circularly polarized antennas can almost realize an SIR of more than 40 dB. Significant improvement can be also observed in the scenario with the existence of backhaul links, where the conventional system had difficulty achieving our system design goal SIR of 16.8 dB, while the proposed antenna architecture could easily attain this goal in most regions of our evaluation ranges.

Lightweight Machine Learning for Digital Cross-Link Interference Cancellation With RF Chain Characteristics in Flexible Duplex MIMO Systems

The flexible duplex (FD) technique, including dynamic time-division duplex (D-TDD) and dynamic frequency-division duplex (D-FDD), is regarded as a promising solution to achieving a more flexible uplink/downlink transmission in 5G-Advanced or 6G mobile communication systems. However, it may introduce serious cross-link interference (CLI). For better mitigating the impact of CLI, we first present a more realistic base station (BS)-to-BS channel model incorporating the radio frequency (RF) chain characteristics, which exhibit a hardware-dependent nonlinear property, and hence the accuracy of conventional channel modelling is inadequate for CLI cancellation. Then, we propose a channel parameter estimation based polynomial CLI canceller and two machine learning (ML) based CLI cancellers that use the lightweight feedforward neural network (FNN). Our simulation results and analysis show that the ML based CLI cancellers achieve notable performance improvement and dramatic reduction of computational complexity, in comparison with the polynomial CLI canceller.

Joint Energy Harvesting and Transmission Optimization for Cell-Free Massive MIMO With Network-Assisted Full Duplexing

This paper investigates the problem of joint energy harvesting (EH) and transmission optimization for cell-free massive MIMO with network-assisted full duplexing (NAFD), where each access point (AP) works in full-duplex mode, half-duplex mode or another flexible mode and is connected to a central processing unit (CPU) via compressed fronthaul links. The high demand on the fronthaul links and series cross-link interference (CLI) are the two main problems in cell-free massive MIMO with NAFD. Therefore, in our scheme, we propose a joint strategy of EH, fronthaul compression, and CLI cancelation to maximize the energy efficiency (EE) of the system under constraints of guaranteed quality-of-service (QoS), EH and compressed fronthaul requirements. A two-stage strategy of EH and transceiver design is proposed to solve the complicated optimization problem. Specifically, in the first stage, we propose an EH/information receiving (IR) antenna selection algorithm to design the operation mode of the antennas for uplink users and receiving APs. In the second stage, with the antennas selected in the first stage, we further attempt to solve the EE maximization problem. Furthermore, to solve the highly nonconvex EE maximization problem, we propose a fractional programming (FP)-based two-tier iterative algorithm in which a series of nonconvex–convex approximation methods, such as FP, iterative convex approximation and equivalent formulation, are used. Simulation results demonstrate that the proposed algorithms yield a higher EE gain than the traditional time-division duplexing (TDD) and co-frequency co-time full duplexing (CCFD) schemes.

Efficient coordination of radio frames to mitigate cross-link interference in 5G D-TDD systems

Dynamic time division duplexing (D-TDD) is widely used in 5G to support various services and short-latency communications, where uplink (UL) and downlink (DL) traffic may be highly asymmetric and fast-varying. In particular, D-TDD allows each cell to arrange subframes in terms of selecting link directions, which betters the utilization of spectrum resources based on instantaneous traffic demand. However, the inter-cell subframe misalignment, which is caused by different link directions on the same frequency band in neighboring cells, leads to notable cross-link interference (CLI). Especially, CLI has a negative impact on UL performance. Hence, this paper proposes a cluster-based radio frame coordination using codebooks (CRCC) framework to mitigate CLI efficiently. CRCC first clusters cells and formulates a codebook of radio frame configuration for each cluster, where cells pick their configuration of subframes. Then, the cluster is divided into subclusters, where the cells in each subcluster adjust subframes to reduce misalignments. Finally, CRCC combines subclusters by deciding the subframes of those cells located on the boundaries between subclusters. Simulation results reveal that CRCC greatly increases UL throughput and keeps high DL throughput, thereby improving the performance of a 5G D-TDD system.

Performance analysis of full-duplex densely distributed MIMO with wireless backhaul

In this paper, the spectral efficiency of a full-duplex (FD) densely distributed multi-input multi-output (MIMO) system with wireless backhaul is considered. In-band full-duplex (IBFD) backhauling, in which the backhaul and access transmissions take place on the same spectrum, is exploited for wireless backhauling to enable an efficient spectrum reuse. However, the severe cross-tier interference and cross-link interference reduce the gains of IBFD backhauling. To evaluate the achievable spectral efficiency with imperfect channel state information (CSI), we propose a two-phase channel estimation scheme to estimate the CSI for two wireless links, and the scheme estimates an effective interference CSI between access points (APs) based on beamforming training to perform interference cancelation at APs. Given the estimated CSI, the closed-form expressions of the uplink and downlink achievable rates with maximum ratio transmission beamforming and maximum ratio combining receivers, respectively, are derived with Gamma approximation. Numerical results verify the accuracy of the derived closed-form expressions and the effectiveness of the two-phase channel estimation scheme for interference cancelation. Moreover, compared with half-duplex densely distributed MIMO systems, FD systems with interference cancelation have a better performance.

A QoS-Adaptive Interference Alignment Technique for In-Band Full-Duplex Multi-Antenna Cellular Networks

In this paper, we propose a novel interference alignment (IA) technique for an in-band full-duplex (IBFD) multiple-input multiple-output (MIMO) cellular network where a base station (BS) and user equipment (UE) are equipped with multiple antennas, and the local channel state information (CSI) is available at all nodes. Considering a practical IBFD MIMO cellular network, it is assumed that only the BS operates with full-duplex (FD) communication while UE operate in half-duplex (HD) mode. These IBFD networks introduce a new type of interference called cross-link interference (CLI), in which uplink UE affects downlink UE. The proposed IA technique consists of two symmetric IA schemes according to the number of antennas in the uplink and downlink UE, and both schemes effectively mitigate CLI in the IBFD MIMO network. It is worth noting that both IA schemes are adaptively applicable according to the network's quality-of-service (QoS) requirements, such as uplink and downlink traffic demands. Furthermore, we theoretically characterize and prove the achievable sum-degrees-of-freedom (DoF) of the proposed IA technique. Simulation results show that the proposed IA technique significantly improves the sum rate performance compared to conventional HD communications (multi-user MIMO) while achieving the same achievable DoF as the interference-free IBFD MIMO network.

Analytical Model of Multi-Link Operation in Saturated Heterogeneous Wi-Fi 7 Networks

The upcoming IEEE 802.11be standard, known as Wi-Fi 7, introduces the multi-link operation, which allows a Wi-Fi device to transmit and receive packets via several links simultaneously. However, in some cases, e.g., when the spectral distance between two channels used by the links is small, cross-link interference caused by the transmission on one link can impair the transmission on another link. 802.11be defines operation rules for this case called the non-simultaneous transmit and receive (NSTR) mode. Particularly, the specification requires simultaneous transmissions on different links to be aligned. Otherwise, the transmission shall be performed on only one link. This letter develops an analytical approach to model NSTR operation and computes the throughput in a saturated network when NSTR multi-link devices coexist with legacy devices.

Interference Mitigation for Non-Overlapping Sub-Band Full Duplex for 5G-Advanced Wireless Networks

With new services emerging in fifth generation (5G)-advanced, the evolution in duplex modes plays an important role to meet more stringent requirements for both downlink (DL) and uplink (UL) transmissions. In this paper, sub-band full duplex (SBFD) at base station (BS) is studied as an attainable evolution of the traditional time division duplex (TDD). Both user equipment (UE) transparent SBFD and UE perceptive SBFD are proposed and studied to serve different types of UEs. To tackle the interference introduced by SBFD, a model including both BS self-interference and cross-link interference (CLI) is presented as a first step, and new interference management schemes are proposed. Three approaches to mitigate BS self-interference, namely the passive suppression, analog interference cancellation and digital interference cancellation are analyzed. A new framework for CLI management is illustrated along with enhancements for interference identification, spatial domain interference coordination and power domain adjustment. To validate the feasibility and performance of the proposed SBFD methods under indoor and dense urban scenarios, system-level simulations (SLSs) are carried out and a proof-of-concept (PoC) is developed for the purpose of obtaining experimental results.

Resource Allocation Algorithm Based on Power Control and Dynamic Transmission Protocol Configuration for HAPS-IMT Integrated System

The high altitude platform station (HAPS) system is an essential component of the air-based network. It can shorten transmission delay and make a better user experience compared with satellite networks, and it can also be easily deployed and cover a larger area compared with international mobile telecommunications (IMT). In order to meet the needs of users with asymmetric and random data flow, the spectrum sharing and dynamic time division duplexing (TDD) mode are used in HAPS-IMT heterogeneous network. However, the cross-link interference brought by TDD mode will lead to the degradation of system performance. In this paper, a resource allocation algorithm based on power control and dynamic transmission protocol configuration is proposed. Firstly, a specific timeslot, “low power almost-bank subframe (LP-ABS)”, is introduced into the frame structure of the HAPS physical layer. The transmission protocol designing could mitigate inter-layer interference efficiently by power control in “LP-ABS”. Secondly, the utilization function is adopted for assessing the system performance, which gives attention to both diversified requirements on the quality of services (QoS) and the throughput of the HAPS-IMT system. Simulation results show that power control and resource allocation technologies proposed in this paper can effectively improve system performance and user satisfaction.

Advancements in 5G New Radio TDD Cross Link Interference Mitigation

This article presents enhancements that further improve the performance of 5G New Radio time division duplex (TDD) operation and performance. The focus is on mechanisms to mitigate co-channel cross link interference (CLI) between neighboring cells, providing pointers also to recent advances in remote interference mitigation between cells separated by tens to hundreds of kilometers. A sophisticated framework where User Equipment's (UEs) are used as sensors detecting CLI problems is outlined, and the underlying design rationales are presented. Solutions for simple coordination of TDD radio frame configurations between network elements are described. Solutions based on simple reinforcement learning algorithms for the network to adjust the TDD radio frame configuration are proposed, and validated for both macro and indoor factory deployments, considering both ultra-reliable low latency communication (URLLC) and enhanced mobile broadband (eMBB) traffic. Results from extensive dynamic system-level simulations confirm that such solutions offer attractive benefits.

Full Duplex and Dynamic TDD: Pushing the Limits of Spectrum Reuse in Multi-Cell Communications

Although in cellular networks full duplex and dynamic time-division duplexing promise increased spectrum efficiency, their potential is so far challenged by increased interference. While previous studies have shown that self-interference can be suppressed to a sufficient level, we show that the cross-link interference for both duplexing modes, especially from base station to base station, is the remaining challenge in multi-cell networks, restricting the uplink performance. Using beamforming techniques of low complexity, we show that this interference can be mitigated, and that full duplex and dynamic time-division duplexing can substantially increase the capacity of multi-cell networks. Our results suggest that if we can control the cross-link interference in full duplex, we can almost double the multi-cell network capacity as well as user throughput. Therefore, the techniques in this article have the potential to enable a smooth introduction of full duplex into cellular systems.

Interference Handling Challenges toward Full Duplex Evolution in 5G and Beyond Cellular Networks

Full duplex is a scheme that changes the duplexing paradigm in wireless communication networks. Enabled by self-interference cancellation methodology, it unlocks the potential to improve frequency utilization efficiency and reduce resource allocation latency. However, embracing the full duplex scheme in a mobile network can lead to complications in terms of cross-link interference among network entities. As a matter of fact, a successful network integration for the scheme must consider handling these emerging types of interference. On the other hand, diversification in evolving 5G networks - struggling to address unprecedented broad demands - allows the opportunity to consider full duplex operation at a newly emerging network entity type, which is the integrated access and backhaul (IAB) node. Indeed, this might be the beginning of a network adoption series for the scheme. For instance, the non-terrestrial network, another newly emerging use case, can be the next to benefit from full duplex resource utilization. On the matter of standardized solutions, 3GPP has specified several cross-link interference handling mechanisms, which eases the integration process of the scheme at the network infrastructure level, and paves the way for later phases of user equipment adoption. This incremental network adoption ensures the required technological maturity of self-interference cancellation. In practical terms, self-interference cancellation requirements depend on device type and its deployment environment. As the environment defines the properties of the self-interference channel, it must be known to the self-interference canceller. To assess the full duplex adoption feasibility in the IAB use case, we present experimental study outcomes of self-interference channel measurement addressing the outdoor deployment scenario of an IAB node.

Decentralized Slot-Ordered Cross Link Interference Control Scheme for Dynamic Time Division Duplexing (TDD) in 5G Cellular System

Dynamic time-division duplexing (TDD) allows for flexible resource allocation for the varying downlink (DL) and uplink (UL) traffic demands in the 5G cellular network. It becomes more useful when the number of active users is highly limited, especially for the small cells in a ultra-dense network. However, traffic imbalance between DL and UL in adjacent cells incurs crosslink interference (CLI), which may seriously reduce the system throughput. In order to deal with CLI induced by dynamic TDD, full or partial information on slot assignment and/or mutual interference must be shared among all cells for coordinating dynamic slot assignment throughout the system. In this paper, we propose the fully decentralized slot assignment policies that can reduce the CLI without resorting to side information shared among the cells. It is based a bi-directional slot-ordered scheduling scheme in each subframe, which exploits implicit location-dependent information such as signal-to-interference-plus-noise ratio (SINR) and/or three-dimensional spatial angle for all UEs in each cell under a full-dimension multi-input and multi-output (FD-MIMO) operation. Our system-level performance evaluation in 5G system scenario has shown that the proposed approach can maintain total interference almost constant even subject to the CLI. Furthermore, it achieves the average system throughput as much as 95% and 91% of the performance that can be achieved by a centralized greedy search for DL and UL, respectively, without much compromising the lower 5% system throughput.

Network-Assisted Full-Duplex Distributed Massive MIMO Systems With Beamforming Training Based CSI Estimation

Network-assisted full-duplex (NAFD) distributed massive multiple-input multiple-output (MIMO) systems enable simultaneous uplink and downlink communications by dynamically allocating the numbers of uplink and downlink remote antenna units (RAUs), which potentially improve the spectral efficiency in wireless communications. In such systems, channel state information (CSI) plays a critical role in uplink reception and downlink transmission, as well as the cross link interference cancelation caused by downlink RAUs to uplink RAUs. Moreover, downlink terminals need to estimate CSI to reliably decode the received signals due to the reduced channel hardening effect. However, high training overhead makes it generally impossible to directly estimate CSI. This paper proposes to estimate effective CSI (inner products of beamforming and channel vectors) instead based on beamforming training scheme. Under this scheme, we derive closed-form expressions for uplink and downlink achievable rates with different receivers and beamforming. Given these expressions, we propose an efficient power allocation scheme which is only dependent on slowly varying large-scale fading from the perspective of multi-objective optimization. Numerical results verify the accuracy of the derived closed-form expressions and effectiveness of beamforming training based CSI estimation. Moreover, trade-off regions between the considered optimization objectives under various system parameters offer numerous flexibilities for system optimization.