Link Interference Research Articles

Optimal Power Control in Cognitive Satellite Terrestrial Networks With Imperfect Channel State Information

To address the spectrum scarcity in future satellite communications, employing the cognitive technique in the satellite systems is considered as a promising candidate, which leads to an advanced architecture known as cognitive satellite terrestrial networks. Power control is a significant research challenge in cognitive satellite terrestrial networks, especially when the perfect channel state information (CSI) of satellite or terrestrial links is unavailable. In this context, we investigate the impact of imperfect CSI of both desired satellite link and harmful terrestrial interference link on the power control scheme in cognitive satellite terrestrial networks. By adopting a pilot-based channel estimation of satellite link and a back-off interference power constraint of terrestrial interference link, a novel power control scheme is presented to maximize the outage capacity of the satellite user while guaranteeing the communication quality of primary terrestrial user. Extensive numerical results quantitatively demonstrate the effect of various system parameters on the proposed power control scheme in cognitive satellite terrestrial networks with imperfect CSI.

Using Cell‐Phone Tower Signals for Detecting the Precursors of Fog

AbstractIn the last decade, published research has indicated the potential of commercial microwave links that comprise the data transmission infrastructure of cellular communication networks as an environmental monitoring technology. Different weather phenomena cause interference in the wireless communication links that can therefore essentially act as a low‐cost sensor network, already deployed worldwide, for atmospheric monitoring. In this study we focus on the attenuation effect caused in commercial microwave networks due to gradients in the atmospheric refractive index with altitude as a result of the combination of temperature inversions and falls in the atmospheric humidity trapped beneath them. These conditions, when combined with high relative humidity near ground level, are precursors to the creation of fog. The current work utilizes this novel approach to demonstrate the potential for detecting these preconditions of fog, a phenomenon associated with severe visibility limitations that can lead to dangerous accidents, injuries, and loss of lives.

Enhanced Service Discovery Model for Wireless Mesh Networks

Wireless mesh networks (WMNs) are the only cost-effective networks that support seamless connectivity, wide area network (WAN) coverage, and mobility features. However, the rapid increase in the number of users on these networks has brought an upsurge in competition for available resources and services. Consequently, factors such as link congestion, data collisions, link interferences, etc. are likely to occur during service discovery on these networks. This further degrades their quality of service (QoS). Therefore, the quick and timely discovery of these services becomes an essential parameter in optimizing the performance of service discovery on WMNs. In this paper, we present the design and implementation of an enhanced service discovery model that solves the performance bottleneck incurred by service discovery on WMNs. The proposed model integrates the particle swarm optimization (PSO) and ant colony optimization (ACO) algorithms to improve QoS. We use the PSO algorithm to assign different priorities to services on the network. On the other hand, we use the ACO algorithm to effectively establish the most cost-effective path whenever each transmitter has to be searched to identify whether it possesses the requested service(s). Furthermore, we design and implement the link congestion reduction (LCR) algorithm to define the number of service receivers to be granted access to services simultaneously. We simulate, test, and evaluate the proposed model in Network Simulator 2 (NS2), against ant colony-based multi constraints, QoS-aware service selection (QSS), and FLEXIble Mesh Service Discovery (FLEXI-MSD) models. The results show an average service discovery throughput of 80%, service availability of 96%, service discovery delay of 1.8 s, and success probability of service selection of 89%.

Iterative Intercell Interference Cancellation in MIMO Multicell Networks

An iterative intercell interference cancellation algorithm is introduced to improve the receiver performance of uplink transmission in multicell networks. At first, the uplink signal detection is performed independently in each cell according to minimum mean squared error (MMSE) criterion. Subsequently, the detection results are applied to reconstruct the transmit signals of different users and cancel their interference to neighboring cells. With the help of reconstruction results, the MMSE detection matrix of each cell is updated. The channel responses of both efficient and interference links are estimated with the help of pilots. The pilot allocation parameter is introduced to indicate the quality of channel estimation. The simulation results indicate that intercell interference can be greatly mitigated by the proposed algorithm with a moderate number of receiver antennas at the base station.

Feasibility-Aware Partial Interference Alignment for Hybrid D2D and Cellular Communication Networks

Device-to-Device (D2D) communication has been a promising technology for the fifth generation (5G) wireless network owing to the higher throughput, less energy consumption, and lower latency. As the 5G network becomes denser, the interference in a hybrid D2D and cellular communication system becomes much severe and more difficult to deal with. In this paper, a novel feasibility aware partial interference alignment (FA-PIA) scheme is investigated. Partial IA has already been studied to manage severe interference for symmetric interference network or simple asymmetric network with limited users. In this paper, we consider an asymmetric interference network with an arbitrary number of D2D users transmitting concurrently. We aim to boost the degrees of freedom and achievable sum rate. To achieve this goal, a lower complexity three-step-based scheme is proposed. Specifically, the pressure transfer tree-based interference selection algorithm is first developed, which is to select the appropriate interference links to be aligned under the IA feasibility constraints. Then, the minimum interference leakage-based iterative partial IA scheme is given to mitigate the selected interference. At last, a constrained concave convex procedure-based iterative power optimization algorithm is provided to further manage the residual interference. Numerical results demonstrate that the proposed three-step-based FA-PIA scheme can significantly improve the achievable sum rate.

Inter-Area Interference Modeling in Distributed Wireless Mobile Ad Hoc Networks

Distributed wireless mobile ad hoc network has superiority of flexible networking, powerful extensibility, and low cost of operation and maintenance. Compared with the centralized ones, the distributed network can effectively solve a series of problems, such as the increase in operation and maintenance costs, the complex setting of center nodes, performance deterioration in large-scale scenarios, and hard to optimize routing. It has broad application prospects in ultra-dense networks of fifth-generation, distributed device-to-device communication, and industrial wireless sensor networks. Due to the absence of a control center, interference coordination in distributed network can only rely on the maintenance of neighbors. This paper first establishes the model of link interference and successful transmission probability under different hops of neighbor maintenance. We discover that the existing protocols with two-hop neighbor maintenance have serious inter-area interference which can jeopardize the performance, and maintaining three-hop neighbors have a 6-dB gain of receivers’ signal interference ratio. Hereby, this paper proposes and verifies a scheduling and channel reuse protocol under three-hop neighbor maintenance, laying a solid foundation for the practical application of distributed network.

A Multi-Radio Multi-Channel Assignment Algorithm Based on Topology Control and Link Interference Weight for a Power Distribution Wireless Mesh Network

In this paper, a multi-radio multi-channel (MRMC) assignment algorithm based on topology control and link interference weight for power distribution wireless mesh networks is developed. Firstly, topology control is adopted to achieve the minimum power transmission in the network, then the load weight for each link is calculated with the expected load in each network node. Secondly, the link interference weight is derived, it’s turned out being related to the load weight and interference of the link. Finally, the MRMC is assigned using our proposed algorithm. A practical power distribution scenario in Dongying city, China, is used to establish the network topology, then we use NS-2 simulation platform to verify the algorithm proposed in this paper. Simulation results show that our proposed algorithm is with much smaller average delay and delay variations as well as larger throughput compared with two typical algorithms available.

Linear Interference Alignment in Full-Duplex MIMO Networks With Imperfect CSI

In this paper, we consider a system where full-duplex (FD) base-stations (BSs) communicate with half-duplex (HD) downlink (DL) and uplink (UL) users in a multi-user multi-cell network, where all nodes are equipped with multiple antennas. The introduction of FD BSs offers potential to increase spectral efficiency, however, it also causes a surge in the number of interference links compared with the HD network counterpart. Here, we apply linear interference alignment (IA) to manage interference in this network under imperfect channel state information (CSI). First, we characterize the performance losses incurred with respect to the achievable sum rate and degrees of freedom (DoFs). Results show that the general trend in performance loss is mainly determined by how the error scales with the signal-to-noise ratio (SNR). In particular, full UL and DL DoF can be achieved even under imperfect CSI when the channel error is at least inversely proportional to SNR. Moreover, in such cases the sum rate loss is always finite, and either goes to zero or is upper bounded by a derived value. Second, we design two linear IA algorithms applicable to the system under consideration. These are based on minimizing the mean square error (MMSE) and maximizing the signal-to-interference-plus-noise ratio, and consider statistical knowledge of the CSI error for added robustness. The proposed algorithms follow specific design principles that distribute the different interference components amongst the various beamformers and result in unitary receivers and precoders. In addition, we show that under certain conditions both designs result in identical beamforming solutions, even though the MMSE algorithm has lower computational complexity. Finally, we also derive the proper condition for IA feasibility in the multi-cell system under consideration.

Deployable mechanisms constructed by connecting orthogonal Bricard linkages, 8R or 10R single-loop linkages using S joints

This paper is to propose a novel construction method for constructing a family of over-constrained multi-loop deployable mechanisms by connecting orthogonal single-loop linkages using spherical (S) joints. An orthogonal single-loop linkage refers to a linkage with an even number of identical links with orthogonal revolute (R)-joint axes and no offset. Two types of multi-loop mechanisms are obtained, including parallel mechanisms (PMs) and loop-coupled mechanisms (LCMs) by connecting orthogonal Bricard linkage, 8R or 10R linkage platforms. The mechanisms constructed by orthogonal Bricard linkages only have one degree-of-freedom (DOF). The volume of the PM is calculated, which indicates that the mechanisms have a high ratio of stowed-to-deployed diameter, without considering link interference. The mechanisms designed using orthogonal 8R or 10R linkages have multiple motion modes and can switch between different modes through singular positions. Finally, the method has been extended to the PMs and LCMs composed of loops that the axes of two adjacent R joints are not perpendicular to each other.

Outage and Diversity Analysis of Underlay Cognitive Mixed RF-FSO Cooperative Systems

We investigate the performance of asymmetric radio frequency (RF) and free-space optical (FSO) dual-hop cognitive amplify-and-forward relay networks where RF links are subject to independent and nonidentically distributed Nakagami-m fading. We consider that the RF link transmitter and receiver are secondary users of an underlay cognitive network. Specifically, the transmit power conditions of the proposed spectrum-sharing network are governed by either the combined power constraint of the interference on the primary network and the maximum transmission power at the secondary network, or the single power constraint of the interference on the primary network. Also, we consider a double generalized gamma fading channel with pointing error and both heterodyne and intensity modulation/direct detection methods in the FSO link. The closed-form and asymptotic expressions of outage probability for this system are calculated for fixed gain and channel-state-informationassisted relaying techniques. It is demonstrated that the diversity order is a function of the fading severity of the RF link, turbulence parameters of the FSO link, and pointing error, regardless of the interference channel parameter of the primary user. However, the coding gain is impressed by the interference link parameter and RF-FSO links parameters. The diversity-multiplexing trade-off analysis is done for this network, where we show that this trade-off is independent of the primary network.

Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks.

This paper proposes novel satellite-based wireless sensor networks (WSNs), which integrate the WSN with the cognitive satellite terrestrial network. Having the ability to provide seamless network access and alleviate the spectrum scarcity, cognitive satellite terrestrial networks are considered as a promising candidate for future wireless networks with emerging requirements of ubiquitous broadband applications and increasing demand for spectral resources. With the emerging environmental and energy cost concerns in communication systems, explicit concerns on energy efficient resource allocation in satellite networks have also recently received considerable attention. In this regard, this paper proposes energy-efficient optimal power allocation schemes in the cognitive satellite terrestrial networks for non-real-time and real-time applications, respectively, which maximize the energy efficiency (EE) of the cognitive satellite user while guaranteeing the interference at the primary terrestrial user below an acceptable level. Specifically, average interference power (AIP) constraint is employed to protect the communication quality of the primary terrestrial user while average transmit power (ATP) or peak transmit power (PTP) constraint is adopted to regulate the transmit power of the satellite user. Since the energy-efficient power allocation optimization problem belongs to the nonlinear concave fractional programming problem, we solve it by combining Dinkelbach’s method with Lagrange duality method. Simulation results demonstrate that the fading severity of the terrestrial interference link is favorable to the satellite user who can achieve EE gain under the ATP constraint comparing to the PTP constraint.

A Closed-Form Expression to Evaluate Nonlinear Interference in Raman-Amplified Links

An accurate, closed-form expression to evaluate the nonlinear interference (NLI) noise power in Nyquist-spaced, coherent optical communication systems using backward-pumped Raman amplification is presented. This enables rapid estimation of the signal-to-noise ratio (SNR) and avoids the need of integral evaluations and split-step simulations. The accuracy of the proposed formula is compared to numerical integration of the Gaussian noise (GN) model and split-step simulations over a wide range of parameters, including three different fiber types. Additionally, the impact of pump depletion on the NLI noise power is studied and the formula is applied to a second-order Raman-amplified system. In the case of first-order amplification and negligible pump depletion, a maximum deviation of 0.34 dB in NLI coefficient between the GN model and the closed-form formula is found, which corresponds to a maximum deviation of $\sim$ 0.1 dB in optimal SNR or similar figures of merit (e.g., maximum reach). When pump depletion is considered, it is shown that the NLI coefficient becomes a function of launch power and as a result the cubic power dependence of the NLI noise power is no longer valid in such regimes. Finally, for the second-order Raman-amplified system, a maximum deviation of 0.39 dB in NLI coefficient is reported.

Precoding for MIMO Channels in Cognitive Radio Networks with CSI Uncertainties and for MIMO Compound Capacity

Inaccurate knowledge of channel state information (CSI) limits the performance offered by multiple-input multiple-output (MIMO) communications. The design of a MIMO precoder needs to take the CSI uncertainty into consideration to mitigate its effects. This paper proposes a method to design the precoder for a secondary user in an underlay cognitive radio framework that maximizes its transmission performance, where the direct link to its receiver and the interference link to a primary user have CSI uncertainties. We model the CSI uncertainties through the Schatten norm that encompasses most commonly used norm measures such as the spectral and Frobenious norms. The proposed method solves iteratively a minimax problem by deriving the optimal solution for the worst case interference CSI uncertainty, applying the alternate-iterate technique for the worst case direct link CSI deviation, and developing a feasible direction projected subgradient technique for the precoder. Simpler solutions for the precoder are also derived under some specific norm measure of CSI uncertainty and certain requirement of transmission power. Simulations corroborate the expected performance of the proposed design.

When mmWave Communications Meet Network Densification: A Scalable Interference Coordination Perspective

The millimeter-wave (mmWave) communication is envisioned to provide orders of magnitude capacity improvement. However, it is challenging to realize a sufficient link margin due to high path loss and blockages. To address this difficulty, in this paper, we explore the potential gain of ultra-densification for enhancing mmWave communications from a network-level perspective. By deploying the mmWave base stations (BSs) in an extremely dense and amorphous fashion, the access distance is reduced and the choice of serving BSs is enriched for each user, which are intuitively effective for mitigating the propagation loss and blockages. Nevertheless, co-channel interference under this model will become a performance-limiting factor. To solve this problem, we propose a large-scale channel state information (CSI) based interference coordination approach. Note that the large-scale CSI is highly location-dependent, and can be obtained with a quite low cost. Thus, the scalability of the proposed coordination framework can be guaranteed. Particularly, using only the large-scale CSI of interference links, a coordinated frequency resource block allocation problem is formulated for maximizing the minimum achievable rate of the users, which is uncovered to be a NP-hard integer programming problem. To circumvent this difficulty, a greedy scheme with polynomial-time complexity is proposed by adopting the bisection method and linear integer programming tools. Simulation results demonstrate that the proposed coordination scheme based on large-scale CSI only can still offer substantial gains over the existing methods. Moreover, although the proposed scheme is only guaranteed to converge to a local optimum, it performs well in terms of both user fairness and system efficiency.

Dynamic time slot allocation and stream control for MIMO STDMA in ad hoc networks

Multiple-input multiple-output (MIMO) technologies have been shown to potentially improve the performance of network. Many traditional medium access control (MAC) protocols, such as spatial time division multiple access (STDMA), may not support MIMO technologies directly and not make full use of the feature of MIMO, which may be a limitation in the practical application in ad hoc networks. Therefore, in this paper, we propose a dynamic time slot allocation and stream control for MIMO STDMA (DTSMS) protocol to improve STDMA in performance. Utilizing stream control technology of MIMO and reservation scheme, DTSMS makes improvement on network throughput and avoids the mutual interference of neighbor links. Thus, DTSMS can support both unicast and multicast simultaneously. Moreover, we implement the dynamic time slot allocation scheme in DTSMS to guarantee the transmission efficiency of packets with high cross-layer transmission parameters, such as the packet priority, neighbor node density, or link quality. Utilizing the collected cross-layer information, the proposed scheme allocates time slots for all nodes dynamically according to the changes of network topology and nodes’ transmission parameters. Finally, the effectiveness of the protocol is demonstrated by numerical analysis and simulations. The results show that DTSMS outperforms STDMA in terms of network throughput and delay. Furthermore, compared to our previous TTS-MIMO, DTSMS can decrease the delay of packets with high transmission parameters and improve the quality of service (QoS).

Low-latency Data Gathering with Reliability Guaranteeing in Heterogeneous Wireless Sensor Networks

In order to achieve low-latency and high-reliability data gathering in heterogeneous wireless sensor networks (HWSNs), the problem of multi-channel-based data gathering with minimum latency (MCDGML), which associates with construction of data gathering trees, channel allocation, power assignment of nodes and link scheduling, is formulated as an optimization problem in this paper. Then, the optimization problem is proved to be NP-hard. To make the problem tractable, firstly, a multi-channel-based low-latency (MCLL) algorithm that constructs data gathering trees is proposed by optimizing the topology of nodes. Secondly, a maximum links scheduling (MLS) algorithm is proposed to further reduce the latency of data gathering, which ensures that the signal to interference plus noise ratio (SINR) of all scheduled links is not less than a certain threshold to guarantee the reliability of links. In addition, considering the interruption problem of data gathering caused by dead nodes or failed links, a robust mechanism is proposed by selecting certain assistant nodes based on the defined one-hop weight. A number of simulation results show that our algorithms can achieve a lower data gathering latency than some comparable data gathering algorithms while guaranteeing the reliability of links, and a higher packet arrival rate at the sink node can be achieved when the proposed algorithms are performed with the robust mechanism.

Requirements, Design Challenges, and Review of Routing and MAC Protocols for CR-Based Smart Grid Systems

Cognitive radio technology can facilitate communication in smart grid applications through dynamic spectrum access. However, traditional routing and MAC protocols adopted for cognitive radio networks may not be beneficial in CR-based smart grid environments due to large data sizes and variable link quality among different functional blocks of smart grids. The interference and fading in wireless links necessitate efficient routing for reliable low-latency data delivery of smart grid applications. This low-latency data delivery must be achieved while protecting the legitimate primary users. Besides efficient routing, MAC layer protocols should be enhanced to achieve successful data delivery with simultaneous spectrum sensing and duty cycling for energy-efficient operation. In this article, we evaluate the requirements and key design challenges for routing and MAC protocols in the CR-based smart grid. We also provide a review of research carried out to date for routing and MAC protocols for the CR-based smart grid.

Connecting a City by Wireless Backhaul: 3D Spatial Channel Characterization and Modeling Perspectives

The backhaul forwards aggregated traffic from massive users, machines, and sensors to the core network, and is the key infrastructure to facilitate a smart city. The beamforming and spatial multiplexing technologies enable the wireless multipoint-to-point backhaul to connect dense small cell eNodeBs (eNBs) and macrocell eNBs. Because the spatial characteristics of the backhaul channels, such as the angular power spectra and spreads, determine the interference and capacity performance of the backhaul links, accurate 3D channel modeling is vital for the evaluation and comparison of candidate proposals. In this article, the concepts and methodology of spatial channel modeling are first introduced, and the state-of-the-art models developed by the standardization bodies in recent years are surveyed. Then we present a field measurement campaign on the 3D backhaul channels in an urban street, including the channel sounder implementation, field measurement, multipath parameter estimation, and propagation modeling. The Rx of the sounder (emulating a donor eNB) was installed on the rooftop of a five-story building, and the Tx was located along a street and at different altitudes to emulate a relay eNB. The channel angular power spectra in the elevation and azimuth domains were measured, and the impact by the relay�s distance and altitude on the angular spreads was evaluated. In addition, a Laplace model is proposed for the power spectra in both domains. This article not only explains the methodology and implementation of the spatial channel measurement, but also reveals the urban wireless backhaul channel characteristics which are useful for the design and deployment of wireless backhaul for a smart city.

Energy-efficient power control for two-tier femtocell networks with block-fading channels

Femtocell network is an effective technique to improve spectrum utilization and indoor coverage. How to allocate users power while keeping acceptable performance under dynamic environment is still a challenge in practice. In this article, we study the problem of energy efficiency in a two-tier network. The objective of the article is to maximize energy efficiency for the two-tier femtocell network with the consideration of uncertain channels. The complex and dynamic communication environment will lead to the imperfect channel state information. In order to enhance the robustness of the two-tier network, we consider the imperfect channel state information of interference links in block-fading channels using probability constraints. We propose a novel scheme to derive optimal energy efficiency by transforming probability constraints into indicator function. A distributed iterative algorithm is proposed to obtain the optimal power solution. Numerical results illustrate the effectiveness of the proposed power control algorithm.

MISO Networks With Imperfect CSIT: A Topological Rate-Splitting Approach

Recently, the Degrees-of-Freedom (DoF) region of multiple-input-single-output (MISO) networks with imperfect channel state information at the transmitter (CSIT) has attracted significant attentions. An achievable scheme is known as rate-splitting (RS) that integrates common-message-multicasting and private-message-unicasting. In this paper, focusing on the general $K$-cell MISO IC where the CSIT of each interference link has an arbitrary quality of imperfectness, we firstly identify the DoF region achieved by RS. Secondly, we introduce a novel scheme, so called Topological RS (TRS), whose novelties compared to RS lie in a multi-layer structure and transmitting multiple common messages to be decoded by groups of users rather than all users. The design of TRS is motivated by a novel interpretation of the $K$-cell IC with imperfect CSIT as a weighted-sum of a series of partially connected networks. We show that the DoF region achieved by TRS covers that achieved by RS. Also, we find the maximal sum DoF achieved by TRS via hypergraph fractional packing, which yields the best sum DoF so far. Lastly, for a realistic scenario where each user is connected to three dominant transmitters, we identify the sufficient condition where TRS strictly outperforms conventional schemes.