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This paper investigates low-complexity joint interference avoidance and desired link improvement for single-channel allocation in multiuser multiantenna access points (APs) for open-access small cells. It is considered that an active user is equipped with an antenna array that can be used to suppress interference sources but not to provide spatial diversity. On the other hand, the operation of APs can be coordinated to meet design requirements, where each of which can unconditionally utilize assigned physical channels. Moreover, each AP is equipped with uncorrelated antennas that can be reused simultaneously to serve many active users. The analysis provides new approaches to exploit physical channels, transmit antennas, and APs to mitigate interference, while providing the best possible link gain to an active user through the most suitable interference-free channel. The event of concurrent service requests placed by active users on a specific interference-free channel is discussed for either interference avoidance through identifying unshared channels or desired link improvement via multiuser scheduling. The applicability of the approaches to balance downlink loads is explained, and practical scenarios due to imperfect identification of interference-free channels and/or the scheduled user are thoroughly investigated. The developed results are applicable for any statistical and geometric models of the allocated channel to an active user, as well as channel conditions of interference users. They can be used to study various performance measures. Numerical and simulation results are presented to explain some outcomes of this paper. [ABSTRACT FROM PUBLISHER]

To efficiently trade off system sum rate and link fairness, power allocation in wireless spectrum-sharing networks often concentrates upon proportional fairness. The corresponding problem has been proved to be convex for a single tone but NP-hard for more than two tones. However, in the two-tone case, the complexity of the problem for achieving proportional fairness has not been addressed yet. In this paper, we prove that the issue of proportional-fairness optimization for the two-tone situation is NP-hard by reducing the problem of finding the maximum independent set in an undirected graph to it. Moreover, a computationally efficient algorithm is proposed to provide an efficient suboptimal solution. Simulation results are presented to illustrate the effectiveness of our proposal. [ABSTRACT FROM PUBLISHER]

We study multiuser detection for uplink transmissions using only analog beamformers in a millimeter-wave (mm-wave) communication system under a limited scattering environment in this paper. In particular, the successive interference cancelation (SIC)-based detection at a base station (BS) that is equipped with an antenna array is considered with the outputs of analog beamformers. We employ beam selection from a codebook of analog beams for low-complexity analog beamforming in the SIC-based detection and compressive sensing (CS)-based channel estimation that is suitable for the BS that only has analog beamformers. Through simulation results, we can see that the performance of the joint analog beam selection and SIC-based detection is comparable with the performance of the SIC-based detection (with ideal digital beamforming) at the cost of more antenna elements with lower complexity. [ABSTRACT FROM AUTHOR]

Densely deployed cellular wireless networks, which employ small cell technology, are being widely implemented. Mitigating the impact of inter- and intracell signal interferences induced by the operations of these networks is a challenging yet essential task. In this paper, we consider adaptive rate scheduling for a transmitting node, regardless of whether it is a base station (BS) or a mobile user. We aim to maximize the system's throughput through the employment of fractional frequency reuse (FFR) schemes. Each BS employs either an omnidirectional or a directional antenna system. We derive the optimal configuration of the FFR scheme and evaluate the ensuing system's performance behavior under absolute and proportional fairness requirements. To maximize the attained throughput by mobiles, we determine the best method to use to classify cell users into interior and edge mobiles. The bandwidth levels allocated for serving interior and edge mobiles are optimized. We derive approximate closed-form mathematical expressions for calculating the probability distributions of the interference signal levels measured at the destined receivers. We account for the impact of the classification process on intercell interference power levels. Under an absolute fairness requirement, we show that optimally configured FFR schemes lead to much enhanced performance. We show that the optimally configured directional-FFR schemes increase the throughput capacity by a factor of about 60% relative to that obtained by using optimal omnidirectional-FFR schemes. The analyses and simulation results presented in this paper serve to characterize the performance behavior attainable by using such small cell deployed cellular wireless network systems when employing the underlying configurations. [ABSTRACT FROM AUTHOR]

In the presence of perfect channel state information (CSI), the achievable degrees of freedom (DoF) in wireless interference networks can be linearly scaled up with the number of users. Achievability is based on the idea of interference alignment (IA). However, in the presence of imperfect CSI, the sum rate becomes degraded, and full DoF may no longer be achievable. In this paper, we propose novel least squares (LS)- and minimum mean square error (MMSE)-based IA schemes that adaptively design beamformers by relying on the availability of imperfect CSI and knowledge of the channel estimation error variance in advance. Interestingly and unlike the other robust algorithms, the proposed adaptive schemes do not impose extra computational complexity compared to their nonadaptive counterparts. It is shown that the LS-based IA is able to outperform interference leakage minimization algorithms under both perfect and imperfect CSI. Furthermore, we compare the performance of the proposed MMSE-based IA with maximum signal-to-interference-plus-noise ratio (Max-SINR) algorithm. We show that while under perfect CSI, the MMSE-based IA achieves the same performance as that of Max-SINR, the former outperforms the latter under CSI mismatch. Meanwhile, it is shown that the proposed MMSE-based IA needs less CSI to be available and has less computational complexity compared to Max-SINR. [ABSTRACT FROM PUBLISHER]

Recently, multiple concurrent transmission techniques have been proposed for smartly exploiting interference to improve network throughput. This paper considers zero-forcing (ZF) precoding that allows two interfering links to concurrently transmit under certain situations. This paper focuses on identifying appropriate schedule schemes that efficiently utilize the ZF precoding opportunities to improve network throughput. With this motivation, we define novel link models to formulate our concerned problem. We also develop a distributed scheduling algorithm by using belief propagation. Finally, we conduct extensive simulation experiments to evaluate the efficiency of ZF in improving network throughput in multihop wireless networks. Our simulations confirm that intelligently utilizing ZF in multihop networks is very effective in improving throughput. [ABSTRACT FROM PUBLISHER]

In noise-limited cooperative wireless networks, the diversity order of selection combining (SC) is the same as the diversity order of maximal ratio combining (MRC). The contribution of this paper is to report that the diversity order of SC and MRC may be different in the presence of randomly distributed interferers at the destination. More specifically, an amplify-and-forward (AF) dual-branch dual-hop cooperative relaying protocol in the presence of Nakagami- $m$ fading, additive Gaussian noise at the relay, and additive Gaussian noise and symmetric alpha-stable interference at the destination is investigated. By contrasting the diversity order of SC against recent results on the diversity of MRC, it is shown that both combining schemes provide the same diversity order if the distribution of the interference is unknown to the destination (interference-oblivious design) . They may achieve a different diversity order, on the other hand, if the interference can be estimated at the destination (interference-aware design) . Moreover, it is shown that the achievable diversity order depends on the interference in the broadcast and relaying phases being spatially correlated or independent. [ABSTRACT FROM PUBLISHER]

Cognitive radio (CR) vehicular networks are poised to opportunistically use the licensed spectrum for high-bandwidth intervehicular messaging, driver-assist functions, and passenger entertainment services. Recent rulings that mandate the use of spectrum databases have introduced additional challenges in this highly mobile environment, where the CR-enabled vehicles must update their spectrum data frequently and complete the data transfers with roadside base stations (BSs) in very short interaction times. This paper aims to answer two fundamental questions: 1) when to undertake local spectrum sensing, as opposed to accessing spectrum database information at a finite cost overhead; and 2) how to ensure correct packet receptions among the multiple BSs and CR vehicles using fewer slots than the messages that need to be transmitted. The contributions of this paper are twofold: First, we introduce a method of qualifying the correctness of spectrum sensing results using out-of-band 2G spectrum data using experimental results. Second, to the best of our knowledge, this is the first work on applying the concept of interference alignment (IA) in a practical network setting, leading to dramatic reduction in message transmission times. Our approach demonstrates significant reductions in the overhead of direct database queries and improvement in the accuracy of spectrum sensing for mobile vehicles. [ABSTRACT FROM PUBLISHER]

Mobile edge computing (MEC) has attracted great interests as a promising approach to augment computational capabilities of mobile devices. An important issue in the MEC paradigm is computation offloading. In this paper, we propose an integrated framework for computation offloading and interference management in wireless cellular networks with MEC. In this integrated framework, we formulate the computation offloading decision, physical resource block (PRB) allocation, and MEC computation resource allocation as optimization problems. The MEC server makes the offloading decision according to the local computation overhead estimated by all user equipments (UEs) and the offloading overhead estimated by the MEC server itself. Then, the MEC server performs the PRB allocation using the graph coloring method. The outcomes of the offloading decision and PRB allocation are then used to distribute the computation resource of the MEC server to the UEs. Simulation results are presented to show the effectiveness of the proposed scheme with different system parameters. [ABSTRACT FROM AUTHOR]

Recent studies show that the statistical channel state information (SCSI) helps to largely increase the capacity of communication systems when the instantaneous perfect CSI is unavailable. In this paper, we consider multiuser multiple-input-single-output broadcast channels where the transmitter has the knowledge of SCSI. The major issue of concern in our paper is to improve the average group-rate of the whole system by scheduling users over different time slots. With SCSI at the transmitter side, we are able to precode signals and, hence, compute the theoretical achievable group-rate of arbitrary user groups. Based on the group-rates, we propose tier-2 Munkres user scheduling algorithm (T2-MUSA) that leads to higher average group-rate than existing algorithms with generally better fairness. The optimality of the proposed algorithm in energy-fair user scheduling space is proved and we derive a lower bound of a special case to verify the validity of our simulations. In addition, many conventional user scheduling algorithms maintain queue stability by solving a weighted sum-rate (WSR) problem, using queue lengths to represent weight coefficients. Inspired by T2-MUSA, we propose a QoS-based MUSA (QB-MUSA) aimed at stabilizing queue lengths and maximizing throughput. In results, we show that QB-MUSA exhibits higher throughput than the conventional WSR-based algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we introduce advancements of the conventional blanking nonlinearity (BN) for orthogonal frequency-division multiplexing (OFDM)-based systems, which is referred to in the following as advanced BN. Blanking is a common measure for mitigating impulsive interference that often occurs in wireless communication systems. Although the BN removes impulsive interference reliably, it possesses various drawbacks for OFDM-based systems. In particular, the choice of the blanking threshold (BT), to decide whether a received sample is blanked, is a critical issue. We present an algorithm for determining the optimal BT to maximize the signal-to-noise-and-interference ratio (SINR) after blanking. Another drawback is that the entire received signal is discarded during a blanking interval, despite the fact that only a fraction of the spectrum of the OFDM signal might be affected by interference. We show how blanking can be limited to subcarriers that are actually affected by interference. Further, we show how these measures can be combined and how a priori information obtained in an iterative loop can be incorporated into the proposed scheme. Simulation results incorporating realistic channel and interference models demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM PUBLISHER]

This paper proposes feasible and satisfactory system design parameters to mitigate the impact of interference on real-time high-definition video streaming in infrastructure-to-vehicle (I2V) telematic platforms utilizing 60-GHz radiation and the corresponding IEEE 802.11ad baseband. The analysis captures the impact of interference on the 60-GHz I2V vehicle (IV), which is caused by multiple interference sources through the 60-GHz wireless transmissions from nearby I2V base stations (IBSs) to their associated IVs. The impact of the interference on the quality of main 1080p at 30-frame/s (30 1080p frames/s) and 1080p at 60-frame/s (60 1080p frames/s) streaming is analyzed and estimated for various simulation settings. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the anti-jamming channel selection problem for interference mitigation (IM) based dense wireless networks in dynamic environment, in which the active user set is variable due to their specific traffic demands. We jointly consider the mutual interference among users and external jamming in IM-based dense wireless networks, and propose a generalized maximum protocol interference and jamming model to accurately capture the mutual interference and external jamming. Then, the anti-jamming channel selection problem is formulated as an anti-jamming dynamic game, and subsequently it is proved to be an exact potential game, which has at least one pure strategy Nash equilibrium (NE). Based on the stochastic learning theory, a distributed anti-jamming channel selection algorithm (DACSA) is proposed to find the NE solution. Moreover, the simulation results are presented to demonstrate the effectiveness of the proposed DACSA algorithm. [ABSTRACT FROM AUTHOR]

Modern models for public safety networks (PSN) utilize commercial user equipment (UE) and exclusively rely on cellular architecture. This paper introduces a heterogeneous PSN mechanism where multiple wireless protocols are used to establish resilient communications. Specifically, each UE acts as a learning automaton and using a reinforcement-learning approach selects the most appropriate operation protocol, in terms of environment/topology needs, protocol specifications, and PSN battery-life extension. In addition, we follow a UE coalition formation approach, using a Chinese restaurant process that considers UEs’ communication interest, physical distance, and energy availability. Finally, each UE's optimal transmission power is obtained using the formulation of a utility-based power control problem as a non-cooperative, distributed game among UEs, which converges to a unique Nash equilibrium. The performance of the proposed approach is evaluated using modeling and simulation under several scenarios; also, its superiority is demonstrated. [ABSTRACT FROM AUTHOR]

Massive connectivity in the near future puts forward an urgent demand for the accurate time delay estimation (TDE). However, the accuracy of the traditional TDE methods is severely degraded by the multi-path interference (MPI) and multi-device interference. In this paper, we propose a path integration based delay estimation (PRIDE) method. For the first time, the unique delay structure of each device is utilized, and the MPI is converted to an assistance. Considering the practical case where multi-path delays are non-integer times of the sampling period, PRIDE is carried out in two steps to estimate the integer and fractional parts of the delay sequentially. Theoretical analysis and simulations show that the TDE accuracy in the multi-device multi-path environment can be greatly improved by the proposed PRIDE method with comparatively low computational complexity. [ABSTRACT FROM AUTHOR]

Recent advances in loop interference cancelation techniques enable full-duplex relaying (FDR) systems, which transmit and receive simultaneously in the same band with high spectrum efficiency. Meanwhile, wireless virtualization has attracted a lot of attention from both academia and industry because it can provide more flexibility, diversity, and other benefits in the process of wireless network design, construction, operation, and management. In this paper, we introduce the idea of wireless virtualization into FDR cellular networks. Then, the problem of energy-aware virtual resource management is formulated as a three-stage Stackelberg game. The subgame perfect equilibrium for each stage is analyzed. In addition, the interplays of the three-stage game are discussed, and an iterative algorithm is proposed to obtain the Stackelberg equilibrium solution. Simulation results are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we study the effective capacity (EC) of cognitive radio (CR) networks operating under statistical quality-of-service (QoS) constraints in an attempt to support real-time applications at the secondary users (SUs). In particular, we analyze the performance gains, in terms of EC and average transmitted power, attributed to leveraging the primary user (PU) feedback overheard at the SU, at no additional complexity or hardware cost. We characterize the EC performance improvement for the SU, in the presence of a feedback-based sensing scheme, under the signal-to-interference-plus-noise ratio (SINR) interference and collision models. Toward this objective, we develop a Markov chain model for feedback-based sensing to compare the performance of a two-link network, a single secondary link, and a primary network abstracted to a single primary link, with and without primary-feedback exploitation. We prove that exploiting the primary feedback at the secondary transmitter improves the EC of the SU under the SINR interference model. On the other hand, interestingly, exploiting the PU feedback messages does not enhance the EC of the SU under the collision model. Nevertheless, exploiting the PU feedback reduces the SU average transmitted power under the two aforementioned models. Finally, we present numerical results, for plausible scenarios, that support our analytical findings. [ABSTRACT FROM PUBLISHER]

This paper considers a cross-layer optimization framework for video streaming in multinode wireless networks with a time-varying interference environment. We develop a distributed joint power control and rate adaptation framework that exploits the time diversity of the wireless channels, satisfies the hard delay constraints associated with video applications, and respects a certain fairness criterion among the nodes. The proposed framework performs power allocation at the physical/media access control layers to achieve a certain target signal-to-interference-plus-noise ratio, such that the difference between the arrival and the departure rates at the queues is very small, and performs video rate adaptation at the video coding layer (upper layer) according to the nodes' demanded video quality, their channel conditions, and a given fairness criterion. A main challenge here is that the adaptation of the video rate and the power control is not performed at the same time scale. We deal with this issue and model the power and rate variations of the nodes as linear stochastic dynamic equations and formulate a risk-sensitive control problem that captures the hard delay constraints of the video services and the fairness criterion for resource utilization. We provide an optimal solution for this control problem and illustrate the performance of our framework through simulations. [ABSTRACT FROM AUTHOR]

Cognitive radio allows secondary users (SUs) to exploit the underutilized radio spectrum of the primary networks. To fully utilize the primary spectrum and maximize spectral efficiency, overlay and underlay transmissions, which exploit the white and gray spaces, respectively, should be used together. However, for underlay, the SUs need to transmit at low power to avoid causing harmful interference to the primary users (PUs), whereas the PUs will cause high interference to the SUs. Thus, interference mitigation is a major issue in underlay spectrum utilization. In this paper, a hybrid transmission system that exploits both overlay and underlay is proposed using multicarrier code-division multiple access due to its interference rejection and diversity exploitation capabilities. Unlike existing approaches, which separate the use of overlay and underlay spectrum, the proposed schemes utilize the entire spectrum for underlay transmission to minimize the PU interference while using the spectrum holes for overlay transmission to maximize the data rate. Two techniques that operate at full-load and overload scenarios are proposed. The overload system is then extended to the multiuser underlay case to further improve spectrum utilization. [ABSTRACT FROM AUTHOR]

Cognitive radio networks (CRNs) introduce a new communication paradigm that enables unlicensed users to opportunistically access spectrum bands assigned to licensed users. Interestingly, the broadcast problem, which is one of the most fundamental operations in CRNs, has not been well studied. Existing works for the broadcast issue in CRNs are heuristic solutions either without a performance guarantee or with performance far from the optimal solution. In this paper, we study the minimum-latency broadcast scheduling (MLBS) issue for CRNs. Our contributions are threefold. First, we propose a mixed broadcast scheduling (MBS) algorithm under the unit disk graph (UDG) model, denoted by MBS-UDG. MBS-UDG finishes a broadcast task by employing mixed unicast and broadcast communication modes in two phases. We show that the latency performance of MBS-UDG is O(\hbar+\DeltaT) when \DeltaT\leq \1/p or O(\hbar+\log1-p(\1/p\DeltaT)) when \DeltaT>\1/p, where \hbar and \Delta_{T} are the height and the maximum number of leaf nodes connected by a second user (SU)of the broadcasting tree, respectively, and p$ is the spectrum opportunity for a secondary communication. Furthermore, the redundancy performance of MBS-UDG is analyzed. Second, we extend MBS-UDG to a more general MBS algorithm under the protocol interference model and analyze its latency and redundancy performance. Finally, simulations are conducted to validate MBS, which indicate that MBS significantly improves existing algorithms with respect to both latency and redundancy. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate multiuser scheduling with joint user pairing, resource allocation, and power control (PC) in Long-Term Evolution (LTE) uplink cellular networks. We first derive the received signal-to-interference-plus-noise ratio (SINR) in spatial multiuser single-carrier frequency-division multiple-access (SC-FDMA) systems with frequency-domain minimum mean square error (MMSE) equalization. Based on this, we formulate an optimization problem as joint multiuser pairing, resource allocation, and PC to maximize the weighted throughput of the system. We then divide it into a two-step optimization problem, which is suboptimal but significantly reduces the complexity. The two-step problem first performs optimal frequency resource allocation and user pairing for a given transmit power value and then adjusts the transmit power to maximize the weighted throughput when frequency resources are allocated and users are paired. With the help of high-interference indicators exchanged among multiple base stations (BSs), we develop an iterative distributed and low-complexity algorithm to further simplify the two-step problem. System-level simulation results show that the proposed algorithm can effectively mitigate interference and significantly outperforms the existing algorithms. [ABSTRACT FROM PUBLISHER]

This paper analyzes statistical properties of the Poisson line Cox point process useful in the modeling of vehicular networks. The point process is created by a two-stage construction: a Poisson line process to model road infrastructure and independent Poisson point processes, conditionally on the Poisson lines, to model vehicles on the roads. We derive basic properties of the point process, including the general quadratic position of the points, the nearest distance distribution, the Laplace functional, the densities of facets of the Cox–Voronoi tessellation, and the asymptotic behavior of the typical Voronoi cell under vehicular densification. These properties are closely linked to features that are important in vehicular networks. [ABSTRACT FROM AUTHOR]

As an important complement and enhancement technique for cellular communication systems, the device-to-device (D2D) technique has exhibited a number of benefits in terms of, for instance, offering an improved spectral efficiency, enabling a reduced transmit power and providing an enhanced channel capacity, etc. However, a severe interference may be imposed on the conventional cellular users by the activated D2D links, thus, substantially eroding the performance of the former. In this paper, we propose an interference limited area (ILA) based D2D-management scheme along with an appropriately designed power control algorithm for mitigating the above-mentioned interference. We first derive the closed-form expressions of the average coverage probability for both the cellular and D2D links under the proposed ILA scheme, followed by proposing a resource-allocation algorithm subject to a power control mechanism. Numerical results show that the proposed ILA scheme is capable of outperforming the conventional scheme in terms of both the coverage probability (i.e., for both cellular and D2D links) and the sum data rate, particularly in the scenarios with a high D2D density and a high signal-to-interference-plus-noise ratio. [ABSTRACT FROM AUTHOR]

In this paper, we propose a non orthogonal multiple access (NOMA) system using coexisting narrow and wide beams to increase total capacity. In our proposed system, a base station considers the state of user mobility and supports users with either a narrow or a wide beam according to the mobility state. The proposed NOMA system uses the beam gain between a narrow and a wide beam, as well as the power gain from the pathloss difference in NOMA scheme. The system is thus less influenced by user mobility at the point of NOMA pairing. In the proposed system, we consider two power allocation schemes, namely the max and fair power allocation methods, and propose a pairing algorithm to maximize the capacity by minimizing the interference between narrow and wide beam user. The result verifies that the proposed system improves sum throughput, compared with the OMA and conventional NOMA system. [ABSTRACT FROM AUTHOR]

Interference alignment (IA) is a promising technique for interference management in wireless networks. However, most of the existing IA works are based on symmetric multiuser networks. To meet the requirements of practical applications, we consider asymmetric networks where the location of each user is randomly distributed. When the path loss is large, interference may become sufficiently weak, and aligning the interference via IA becomes unnecessary. In this paper, a spectrum-efficient topology management (TM) scheme is proposed for asymmetric interference networks. In this scheme, for a user far away from others, solely adopting spatial multiplexing (SM) as a point-to-point multiple-input and multiple-output subnetwork is more spectrum efficient. On the other hand, for the users close to each other, jointly comprising an IA subnetwork can be the better choice. Thus, we first present the decision criterion, which is used for reinterpreting the network as a graph. Then, the TM scheme is elaborated with the graph theory. In addition, we present the designs of the precoding and decoding matrices for the IA and SM subnetworks. Simulation results show that the proposed TM scheme is much more spectrum efficient than the conventional IA scheme in asymmetric interference networks. [ABSTRACT FROM AUTHOR]

Partial frequency reuse (PFR) is one of the key techniques to improving max-min fairness for cell-edge user equipment in the fourth generation of mobile communication systems. Recently, multilayer PFR schemes have been proposed, which are considered to be a promising evolution of this technique. In this paper, we propose an analytical framework for multilayer PFR scheme design, which uses a triplet to completely describe a given PFR scheme. Then, closed-form expressions of the average spatial capacities of certain typical regions of a cell are derived. Based on a comprehensive analysis using this framework, a novel multilayer PFR scheme is designed, which divides each cell into inner, middle, and outer layers, with two homolographic sublayers for the middle layer. Reuse factors for the three layers are 1, 3/2, and 3, respectively, and an orthogonal division of the spectrum among different layers is guaranteed. Based on our numerical results, this novel scheme outperforms the traditional two-layer PFR scheme in max-min fairness without degrading the average spatial capacity. Compared with several representative multilayer PFR schemes, it achieves a better tradeoff between these two metrics. [ABSTRACT FROM PUBLISHER]

The increasing densification of telecommunications mobile networks raises the compelling problem of exposure to electromagnetic fields (EMF). In this paper, we address the particular concept of heterogeneous networks, where small cells (SCs) are deployed to build up a second layer to the existing macrocell network. SC deployment is shown to be particularly effective in reducing EMF exposure, in addition to capacity enhancement. Previous studies on EMF have focused on the uplink (UL) and downlink (DL) components separately, although they are strongly correlated. Relying on the definition of the exposure index (EI) from the European FP7 Lexnet project, we evaluate the impact on EMF exposure due to SC deployment. Guidelines for EMF-efficient deployment of SCs are first presented and evaluated. Then, a new enhanced intercell interference coordination (eICIC) algorithm using UL and DL metrics to optimize capacity and exposure to EMF is proposed. Static and self-optimizing dynamic implementations of the solution are considered, using a utility function related to the sojourn time of the users. Time-domain and frequency-domain self-optimized eICIC are compared in terms of EMF exposure reduction and capacity enhancement. The eICIC algorithms are combined with a self-optimized coverage range expansion function leading to further reduction of the EI. The proposed solution for optimizing both capacity and exposure to EMF is compared with a capacity-driven solution based on the DL metrics only. Simulation results illustrate the performance gains obtained for the different SC deployment scenarios. [ABSTRACT FROM PUBLISHER]

In emerging heterogeneous networks (HetNets), a wide range of the underlying performance evaluation problems is related to wireless interference characterization and can be reduced to investigating the distribution of a side length in a random triangle. In this paper, we address the task of calculating the side-length distribution in such a triangle determined by the known distributions of its two other sides and the distribution of the angle between them. No restrictions on the distributions of input random variables (RVs) are imposed except for their statistical independence. Our solution delivers a crucial building block for interference analysis in multitier and multiradio HetNets, including mobile device-to-device communication as one of the most extreme interference-limited cases. [ABSTRACT FROM AUTHOR]

Interference alignment (IA) is a promising transmission technology enabling, essentially, the maximum achievable degrees of freedom (DOF) in $K$-user multiple-input–multiple-output (MIMO) interference channels. The ideal DOF of IA systems have been obtained using independent MIMO channels, which is, usually rarely observed in reality, particularly in indoor environments. Therefore, the data sum rate and symbol error-rate of IA are dramatically degraded in real-world scenarios since the correlation between MIMO channels decreases the signal-to-noise ratio (SNR) of the received signal after alignment. For this reason, an acceptable sum rate of IA in real MIMO-orthogonal frequency-division multiplexing (MIMO-OFDM) interference channels was obtained in the literature by modifying the distance between network nodes and the separation between the antennas within each node to minimize the spatial correlation. In this paper, we propose to apply transmit antenna selection to MIMO-OFDM IA systems either through bulk or per-subcarrier selection, aiming at improving the sum-rate and/or error-rate performance under real-world channel circumstances, while keeping the minimum spatial antenna separation of 0.5 wavelengths within each node. Two selection criteria are considered: maximum sum rate (Max-SR) and minimum error rate (Min-ER). To avoid subcarrier imbalance across the antennas of each user, which is caused by per-subcarrier selection, a constrained per-subcarrier antenna selection is operated. Furthermore, a suboptimal antenna selection algorithm is proposed to reduce the computational complexity of the optimal algorithm. An experimental validation of MIMO-OFDM IA with antenna selection in an indoor wireless network scenario is presented. The experimental results are compared with deterministic channels that are synthesized using hybrid electromagnetic (EM) ray-tracing models. Our performance evaluation shows that the practical feasibility of MIMO-OFDM IA systems is significantly increased by antenna selection in real-world scenarios. [ABSTRACT FROM AUTHOR]

We investigate the power-allocation problem in a two-tier femtocell network including a macrocell and multiple femtocells. Due to shadowing and fading effects, at each cell (macrocell or femtocell), the power levels of desired signal and interference signals vary with time. Under this circumstance, one method to achieve transmission quality in the cells is to first get channel state information (CSI) of all desired links and interference links and then perform power allocation. This method has very large communication and computation overhead. In this paper, we focus on power allocation in which the transmit power levels of the users in the cells do not need to change when the wireless channels fluctuate. We formulate a power-allocation problem subject to bounded outage probability in any cell (macrocell or femtocell). The formulated problem has probabilistic constraints. It is hard to have closed-form expressions of the probabilistic constraints. To solve this, we propose novel transformations of the constraints, based on which we obtain constraints in the format of worst-case value-at-risk. Such constraints can be converted to convex constraints, and thus, the research problem is transformed to a convex problem. For the convex problem, we provide an iterative algorithm that converges quickly. We also investigate the case when the channel gain distributions are unknown. Our proposed schemes have the merits of very small communication and computation overhead and are particularly useful in fast-fading environments. [ABSTRACT FROM AUTHOR]

The widely studied network energy efficiency (EE)-optimal problems (NEPs) emphasize optimality of system EE without taking fairness into account. In this paper, we focus on the max–min EE-optimal problem (MEP) by means of power allocation in interference-limited wireless networks. The MEP offers fairness assurance for users in terms of EE by maximizing the EE of the worst-case user. We show that the MEP is NP-hard. Based on generalized fractional programming, we propose a general EE-based update algorithm (EEUA) to tackle the MEP. One key step in the EEUA involves a nonconvex optimization and NP-hard power allocation problem, and we solve it by devising an iterative power allocation algorithm using sequential convex programming. Simulation results exhibit fast convergence, low complexity, and insensitivity to initial values of the proposed algorithms and verify that the MEP guarantees EE fairness among users, as well as reveal the differences between the MEP and the NEP. [ABSTRACT FROM PUBLISHER]

Interference alignment (IA) is a promising technique for interference management in wireless networks. However, the sum rate may fall short of the theoretical maximum, particularly at low signal-to-noise ratio (SNR) levels since IA mainly concentrates on mitigating the interference, instead of improving the quality of desired signal. Moreover, most of the previous works focused on improving spectrum efficiency, but the energy efficiency (EE) aspect is largely ignored. In this paper, an adaptive energy-efficient IA algorithm is proposed through power allocation (PA) and transmission-mode adaptation for green IA-based wireless networks. The PA problem for IA is first analyzed; then, we propose a PA scheme that optimizes the EE of IA-based wireless networks. When the SNR is low, the transmitted power of some users may become zero. Thus, the users with low transmitted power are turned into the sleep mode in our scheme to save energy. The transmitted power and transmission mode of the remaining active users are adapted again to further improve the EE of the network. To guarantee the interests of all the users, fairness among users is also considered in the proposed scheme. Simulation results are presented to show the effectiveness of the proposed algorithm in improving the EE of IA-based wireless networks. [ABSTRACT FROM PUBLISHER]

Recently, heterogeneous network (HetNet) has been introduced as an appropriate strategy to cope with the explosive growth of wireless traffic. To address the issue of severe interference in the HetNet, we can consider interference alignment (IA), which achieves the maximum degrees of freedom (DOFs) in multiple-input–multiple-output (MIMO) interference channels (ICs). However, an anticipated performance of the MIMO IA is difficult to be clarified, particularly with different numbers of antennas across the nodes when designing an appropriate system. In this paper, we thus study antenna configurations for the three-user MIMO IA with respect to the intended data stream tuple, i.e., DOF. For simple analysis, we consider two-tier network with two types of data stream numbers in a system. First, the dimension of the subspace occupied by interference is derived by aligning the interference in the signal space of the MIMO IA. After this, the suitable numbers of antennas are computed depending on the transmitted data stream numbers. Our obtained results provide an insight on how the performance of the MIMO IA is affected as the system configurations change. Furthermore, we discuss how to maximize the performance of such systems when the available numbers of antennas are finite. The actual simulations with an iterative IA confirm the validity of our derived results. [ABSTRACT FROM PUBLISHER]

Heterogeneous wireless networks are considered as promising technologies to improve energy efficiency. In heterogeneous networks, interference management is very important since the interference due to spectrum sharing can significantly degrade overall performance. In the existing work, various resource allocation methods are proposed to either improve energy efficiency or mitigate interference in orthogonal frequency-division multiple access (OFDMA)-based multicell networks. To the best of our knowledge, no research on resource allocation has jointly considered improving energy efficiency and performing interference control, especially using interference power constraint strategies. Furthermore, most existing work assumes that all of the channel state information (CSI) is known completely, which might not be realistic in heterogeneous networks due to the limited capacity of the backhaul links and varied ownership of network devices. In this paper, we propose a game-theoretical scheme using energy-efficient resource allocation and interference pricing for an interference-limited environment in heterogeneous networks. We formulate the problems of resource allocation and interference management as a Stackelberg game with incomplete CSI. A backward induction method is used to analyze the proposed game. A closed-form expression of the Stackelberg equilibrium (SE) is obtained for the proposed game with various interference power constraints. Simulation results are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a new three-user network information flow model, referred to as the triangular multiple-input–multiple-output (MIMO) relay (TMR) channel, which consists of three users and three relays equipped with nU and nR antennas, respectively. Each user sends two independent messages to the other two users via the adjacent relays in two time slots, which are referred to as the multiple-access and broadcast stages. We derive a novel simultaneous signal and interference alignment for the proposed TMR channel in a scenario where there are fewer antennas at each relay than at each user (nR < nU ) . An optimized pseudo-inverse scheme based on an efficient gradient projection algorithm is proposed to solve the simultaneous alignment problem. By deriving a gradient over weighted sum-rate maximization and applying a gradient descent method, the optimal beamforming vectors are obtained to maximize the effective signal-to-noise ratios. Furthermore, to obtain rapid convergence speed and reduce computational complexity, we introduce a quasi-Newton method, which is referred to as the Broyden–Fletcher–Goldfarb–Shanno algorithm, by approximating the Hessian matrix of a pure Newton method. The convergence of the proposed gradient algorithm is guaranteed by proposing a line search algorithm. Finally, a performance evaluation shows that the proposed scheme offers a higher sum rate, produces a better outage probability, and achieves a higher multiplexing gain than the existing schemes. [ABSTRACT FROM PUBLISHER]

For massive multiuser multiple input multiple output (MIMO) (MU-MIMO) systems, pilot contamination (PC) and data interference (DI) are two main factors that affect the accuracy of the superimposed pilot (SP) based channel estimation, provided that the channel coherence time is less than the total number of users. In this paper, to tackle the effect of the PC, we propose a block-diagonal Grassmannian line packing (GLP) approach, in which the specific sequences for different cells are first designed based on the GLP, and then are block-diagonally extended to form the SP matrices for the users in different cells. To also alleviate the effect of DI on the channel estimation, with the designed SP matrices, an iterative channel estimation (ICE) method based on Tikhonov regularization is presented. The impact that the proposed ICE method has on the signal-to-interference-plus-noise ratio with matched filtering receiver is theoretically analyzed. Moreover, the optimal power allocation factor to the SP by maximizing the spectral efficiency (SE) of the target cell is also derived. Numerical results show that the proposed ICE method with the designed SP matrices effectively mitigates the effects of the PC and DI, and hence, improves the accuracy of channel estimation and further the SE of the massive MU-MIMO systems. [ABSTRACT FROM AUTHOR]

A major challenge in designing a spectral co-existence between radar and communication systems is how to simultaneously provide efficient utilization of the shared spectrum while maintaining a reliable performance for both systems. Due to its flexibility in using linear independent waveforms and superiority in terms of target detection and estimation, the collocated multiple-input-multiple-output (MIMO) radars provide a paramount capability in realizing spectrum sharing with communication systems. In this paper, we consider the use of joint transmit and receive beamformers for both the MIMO radar and MIMO communication systems. Specifically, we design a two-tier alternating optimization spectrum sharing framework that is based on interference alignment (IA) approach. The effectiveness of spectrum sharing between radar and communication systems is guaranteed by mitigating the mutual interference signals in the shared spectral band. Subsequently, motivated by the excellent performance provided by IA in different wireless network scenarios, we propose a spectrum sharing framework that consists of a main iterative algorithm with two subalgorithms included within its operation. The first subalgorithm is used to maximize the signal-to-interference-plus-noise ratio of the radar system, whereas the second one is utilized to maximize the average sum-rate of the communication system. The main iterative algorithm is proposed to jointly optimize the transmit and receive beamforming filters of both systems by performing alternating optimization between the two subalgorithms. The convergences of the proposed algorithm and its subalgorithms are numerically verified. Simulation results are provided to confirm the superiority of the proposed framework for both systems. [ABSTRACT FROM AUTHOR]

In this paper, we propose a two-phase non-orthogonal multiple access (NOMA) scheme with cooperative relaying. In the first phase, an access point (AP) linearly combines the signals of near-user $\mathrm U_1$ and far-user $\mathrm U_2$ and then broadcasts the superimposed signal to $\mathrm U_1$ and multiple relays. $\mathrm U_1$ tries to decode its desired data by treating the signal of $\mathrm U_2$ as interference. In a cooperative zone between AP and $\mathrm U_2$ , multiple relays try to decode the signal of $\mathrm U_2$ by decoding and canceling the signal of $\mathrm U_1$. In the second phase, a decodable relay is selected to forward the far-user's signal and, meanwhile, if $\mathrm U_1$ fails to decode its desired signal in the first phase, it will try to decode and cancel the far-user's signal to further decode its desired signal again. We analyze the system throughput and investigate the impacts of various parameters. Numerical results show that our proposed scheme can greatly outperform the time division multiple access and the non-cooperative NOMA schemes in terms of throughput for most system settings. [ABSTRACT FROM AUTHOR]

In this paper, we present a new technique of the symbol error-rate evaluation for quadrature amplitude modulation in communication systems equipped with conventional detectors designed for additive white Gaussian noise (AWGN) model of interference, but operating over a fading environment with arbitrary interference and AWGN. In contrast to many reported methods, the given technique is applicable to arbitrary interference and fading models, and it can efficiently be implemented numerically. These facts make the derived result especially convenient for practical purposes. [ABSTRACT FROM AUTHOR]

This paper investigates decode-and-forward (DF) buffer-aided relay selection for underlay cognitive relay networks (CRNs) in the presence of both primary transmitter and receiver. We propose a novel buffer-aided relay selection scheme for the CRN, where the best relay is selected with the highest signal-to-interference ratio (SIR) among all available source-to-relay and relay-to-destination links while keeping the interference to the primary destination within a certain level. A new closed-form expression for the outage probability of the proposed relay selection scheme is obtained. Both simulation and theoretical results are shown to confirm performance advantage over the conventional max–min relay selection scheme, making the proposed scheme attractive for CRNs. [ABSTRACT FROM AUTHOR]

In this paper, the problem of distributed mode selection, resource allocation, and interference management is studied for device-to-device (D2D) communications underlaying future cellular networks. In existing underlaid D2D communications, the base station (BS) typically assists D2D pairs in selecting a transmission mode to operate in (network-assisted), that is, either cellular, dedicated, or reuse mode. Network-assisted D2D communications assumes the BS has global knowledge of the network, which includes complete channel state information (CSI). However, acquiring global network information causes signaling overhead and network complexity to increase, due to the large number of users in the network. Therefore, we investigate user-assisted D2D communications as a viable solution for D2D communications, in which the BS has partial knowledge of the network (and partial CSI). To address this problem, a cross-layer coalitional (CLC) game is formulated, where D2D pairs and cellular users are clustered into coalitions based on resource allocation/sharing and mode selection, in a fully distributed and autonomous manner. Clustering D2D pairs allows resources to be shared fairly amongst users in a cluster, while also ensuring D2D pairs operate efficiently. To coordinate the interference between cellular and D2D pairs, an interference management subproblem is proposed that schedules D2D pairs reusing cellular user resources, as well as minimizing the transmission power of all users. To solve this game, a distributed algorithm is proposed, which converges to a Nash stable coalition partition that is socially efficient and has a nonempty core. Simulation results show that the proposed approach can effectively cluster D2D pairs into coalitions based on resource allocation and mode selection, which, in turn, reduces network sum power and increases network sum rate across all D2D pairs. [ABSTRACT FROM AUTHOR]

Contention resolution diversity slotted ALOHA (CRDSA) is a promising solution to meet the challenge of designing efficient random access in future wireless networks. In this paper, we consider CRDSA with transmit power diversity where each packet copy from a device is transmitted at a randomly selected power level. This results in interslot received power diversity, which is exploited by employing a signal-to-interference-plus-noise ratio based successive interference cancellation (SIC) receiver. Leveraging edge-weighted bipartite graph representation, we propose a novel graph-based message passing algorithm to model the SIC decoding. We derive an expression to characterize the recovery-error probability of the scheme. We also formulate and solve an optimization problem to determine the optimal transmit power distribution. The results show that by enhancing the capture effect, the optimal transmit power distribution leads to considerable performance improvement. [ABSTRACT FROM AUTHOR]

Multiple linear constraint water filling problem (MLWFP) is solved innovatively in this paper, in which powers allotted to the $T$ resources of the transmitting user maximize the capacity of the transmitting user while controlling the interference to all the surrounded users of the wireless network. MLWFP is solved previously using iterative algorithms that take more number of iterations, thus, increasing the computational complexity. Unlike prior algorithms, the uniqueness of the proposed algorithm is in detecting the tight bounds for the number of nonzero powers $S$. Subsequently, $S$ is calculated from its bounds. This makes it possible for the proposed algorithm to compute $S$ nonzero powers alone (using the closed-form solution), whereas all the prior algorithms find powers iteratively for all $T$ ( $>$ $S$ ) resources. Thus, the worst case computational complexity of the proposed algorithm is reduced manyfold and is considerably lower than that of the prior algorithms by a factor of $O(T^2)$. Simulation results justify the analysis of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the resource allocation problem in two-tier heterogenous networks (HetNets) with massive MIMO, where two frequency bands, cellular frequency band and millimeter wave frequency band, are used for wireless backhaul links. To coordinate the interference among small cells (SCs), SCs are grouped into multiple SC clusters (SCCs), where SC users are jointly served by SC base stations (BSs) (SBSs) belonging to the same SCC. To eliminate the multi-user and inter-tier interference, we propose a block diagonalization based precoding scheme at macro-BS and each SCC, where the transmit precoding matrix for users is projected onto the null space of interference channels. Following this, we formulate a power allocation optimization problem to maximize the downlink sum rate of the system subject to per-SCC power and users’ quality of service requirements. Since the formulated problem is nonconvex, we transform it into a convex one by appropriate approximation, and a constrained concave convex procedure based iterative algorithm is proposed to obtain the solution. Furthermore, we prove that the obtained solution converges to the local optimum. Meanwhile, according to the structure of the original formulated problem, we divide it into multiple subproblems and propose an optimal iterative water-filling algorithm. Next, we extend the original problem with per-SBS power constraint, which results in that the precoding of each SCC has to be redesigned. On this basis, we propose an iterative water-filling algorithm to obtain the optimal power allocation and precoding. Numerical results are presented to verify the performance of our proposed algorithms. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the problems of minimizing sum power and maximizing sum rate for multicell networks with load coupling, where coupling relation occurs among cells due to intercell interference. This coupling relation is characterized by the signal-to-interference-plus-noise ratio (SINR) coupling model with cell load vector and cell power vector as the variables. Due to the nonlinear SINR coupling model, the optimization problems for multicell networks with load coupling is nonconvex. To solve these nonconvex problems, we first consider the optimization problems for single-cell networks. Through variable transformations, the optimization problems can be equivalently transformed into convex problems. By solving the Karush–Kuhn–Tucker, the optimal solutions to power minimization and rate maximization problems can be obtained in closed form. Based on the theoretical findings of optimization problems for single-cell networks, we develop a distributed time allocation and power control algorithm with low complexity for the sum power minimization in multicell networks. This algorithm is proved to be convergent and globally optimal by using the properties of standard interference function. For sum rate optimization in multicell networks, we also provide a distributed algorithm that yields suboptimal solution. Besides, the convergence for this distributed algorithm is proved. Numerical results illustrate the theoretical findings, showing the superiority of our solutions compared to the conventional solution of allocating uniform power for users in the same cell. [ABSTRACT FROM PUBLISHER]

Full-duplex (FD) multiple-input multiple-output relaying has been considered an effective scheme to increase the spectral efficiency for wireless communications. As known, the main problem for the FD system is the cancellation of loop interference (LI). In this paper, we propose using the joint source/relay precoding to reduce the influence of LI. Therein, linear precoders are used at the source and relay, while the minimum mean-squared-error receiver is adopted at the destination. The joint precoder design is complicated when spatial multiplexing is exploited for signal transmission. To solve the problem, we propose an iterative method in which the original problem is split into two subproblems. With some matrix properties, we then show that each subproblem can be formulated as a convex optimization. Finally, a closed-form solution can be obtained with the Karush–Kuhn–Tucker conditions. Using a mean-squared-error upper bound, we also propose a low-complexity method to reduce the computational complexity. The proposed precoders have closed-form expressions, which is a great advantage in real-world implementation. Simulation results show that the proposed methods significantly outperform existing ones. [ABSTRACT FROM AUTHOR]

We investigate coordinated regularized zero-forcing (RZF) precoding for limited feedback multicell multiuser (MU) multiple-input–single-output (MISO) systems. We begin by deriving an approximation to the expected signal-to-interference-plus-noise (SINR) ratio for the proposed scheme with perfect channel direction information (CDI) at the base station (BS). We also derive an expected SINR approximation for limited feedback systems with random vector quantization (RVQ)-based codebook CDI at the BS. Using the expected interference result for the RVQ-based limited feedback CDI, we propose an adaptive feedback bit allocation strategy to minimize the expected interference by partitioning the total number of bits between the serving and out-of-cell interfering channels. Numerical results show that the proposed adaptive feedback bit allocation method offers a spectral efficiency gain over the existing coordinated zero-forcing (ZF) scheme. [ABSTRACT FROM PUBLISHER]

The communication channel power gain to the nearest neighbor of a node in a wireless communication network is not necessarily the largest among all neighbors due to fading. The probability that the $k$th nearest neighbor of a node has the best communication channel with the highest power gain in a 2-D network with homogeneous Poisson distribution of nodes is derived for a general fading environment. The result is specialized to the case where the communication links are modeled as generalized-gamma fading channels. The analytical results are verified and illustrated by computer simulations and numerical results. Some applications of the new theory are also presented. A novel criterion that represents the fading severity, i.e., the generalized amount of fading (GAF) , is defined, and its value as an important measure for fading channels is justified. [ABSTRACT FROM PUBLISHER]

Cognitive radio (CR) is currently one of the most promising solutions for designing spectrum-efficient wireless communication systems. In this paper, we present a greedy cognitive access policy that handles spectrum sensing with the tools of image processing. By means of the Wigner–Ville transform (WVT), we are able to analyze the time and frequency features of the received interference, and represent them on a time–frequency grid as an image in which brightness reveals the spectrum occupancy. According to sensed interference, each secondary user autonomously tries to access the grid following a multiple-division principle, i.e., by properly shaping the signal in the code, time, and frequency domains. In detail, this is realized by processing the WVT to derive the shaping mask (and the matching algorithm) that allows the filling up of the “time spectrum holes.” Numerical simulations and a test-bed implementation show how the proposed scheme outperforms selected state-of-the-art approaches while still presenting an affordable computational cost. [ABSTRACT FROM AUTHOR]

Small-cell network is a promising solution to the high video traffic. However, it has some fundamental problems, i.e., high backhaul cost, quality of experience (QoE), and interference. To address these issues, we propose a cooperative transmission strategy for video transmission in small-cell networks with caching. In the scheme, each video file is encoded into segments using a maximum distance separable rateless code. Then, a portion of each segment is cached at a certain small-cell base station (SBS), so that the SBSs can cooperatively transmit these segments to users without incurring high backhaul cost. QoE When there is only one active user in the network, a greedy algorithm is utilized to deliver the video-file segment from the SBS with good channel state to the user watching videos in real time. This reduces video freezes and improves the QoE. When there exist several active users, interference will appear among them. To deal with interference, interference alignment (IA) is adopted. Based on the scheme for a single user, the greedy algorithm and IA are combined to transmit video-file segments to these users, and the performance of the system can be significantly improved. Simulation results are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]