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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]

In this paper, we investigate the problem of spectrum leasing in cognitive radio (CR) networks, while incorporating two advanced physical-layer technologies, i.e., multiple-input multiple-output (MIMO) and distributed interference alignment. We present a cooperative spectrum leasing scheme for primary and secondary users to balance the tension between data transmission and revenue collection/payment. A Stackelberg game is formulated, where the primary user is the leader, and secondary users are followers. With backward induction, we derive the optimal strategies for primary and secondary users that can achieve the unique Stackelberg equilibrium, where no player can gain by a unilaterally changing strategy. We find that spectrum leasing is always beneficial to enhancing the utilities of primary and secondary users. The proposed scheme outperforms a no-spectrum-leasing scheme and a cooperative scheme presented in the literature with considerable gains, which demonstrate the benefits of spectrum leasing and distributed interference alignment and validates the efficacy of the proposed scheme. [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]

In vehicle hands-free communication systems and video teleconferencing systems, echoes are typically encountered. Adaptive filters are usually employed to remove the echoes in these applications. However, large outliers and highly correlated speech input signals are two key factors that limit the performance of the adaptive filters. In this paper, we propose an affine projection Versoria (APV) algorithm, which is obtained by maximizing the summation of Versoria-cost reusing with a constraint on the square of the L2-norm of the filter weight vector difference. In this way, the features of the Versoria-cost maximization and data reusing are combined and, consequently, the proposed APV algorithm obtains robustness to the large outliers and accelerates the convergence rate for the correlated input signals. The complexity of the proposed APV algorithm is analyzed and then a fast recursive filtering technique is introduced to reduce its complexity. A stability analysis proves that the proposed APV algorithm is convergent. In addition, an analytical expression of the steady-state excess mean-square error for the proposed APV algorithm has been derived and simulated results are in agreement with the theoretical analysis result. Simulations on echo channel estimation and echo cancellation show that the proposed APV algorithm performs much better than the maximum Versoria criterion, affine projection sign, and affine projection algorithms. [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]

Due to frequent handovers in broadband wireless communications for the high-speed railway system, communication interruption caused by handover failures could seriously degrade the users' experience. Aiming at reducing the handover failure probability, this paper proposes an effective handover scheme based on the distributed antenna system (DAS) and mobile-relay-aided two-link architecture, i.e., ground–relay link and relay–onboard link, where the mobile relay is mounted on top of the moving train. In addition, an antenna selection scheme with optimal power allocation is proposed to improve handover performance. Our simulation and analysis results show that the DAS structure with macrodiversity can reduce the unnecessary handovers, as well as reduce the handover failure and link outage probabilities compared with the traditional cell without DAS. In addition, the proposed DAS with an antenna selection scheme performs better in terms of handover failure and link outage probabilities than that of DAS with a equal power allocation (EPA) scheme. [ABSTRACT FROM PUBLISHER]

Blocking probability is widely used as a performance measure for dimensioning a variety of networks, including wireless communication systems. However, the performance of the system may be affected by factors other than traffic and resources, i.e., the primary ingredients in blocking. Such factors include interference, energy consumption, service delay restriction, and others. In this case, blocking by itself does not fully convey the extent of the system quality of service (QoS). Those other phenomena may lead the system to experience an outage, in which case resources, even if available, cannot be used because of the performance degradation that this may incur. In this paper, we propose a performance measure, i.e., BlockOut probability, that combines blocking and outage in one parameter. Exact, closed-form, and recursive forms of this parameter are presented, and a simple example of application is shown. The BlockOut probability encompasses the well-known Erlang-B formula as a special case. Although the application example focuses on wireless systems, BlockOut may find use in a variety of other networks. [ABSTRACT FROM PUBLISHER]

In this paper, a low-complexity detection scheme is proposed for an underdetermined multiple-input–multiple-output (UD-MIMO) wireless communication system that employs $N$ transmit antennas and M < N$ receive antennas. The proposed scheme combines a simplified parallel interference cancelation (S-PIC) with the block decision feedback equalization (BDFE) algorithm. To account for the extra (N - M)$-dimension in the transmitted signal, the UD-MIMO system is partitioned into two subsystems: one with (N - M)$ transmit antennas and the other one with M sequences in the first subsystem, with $Q$ being the constellation size, the proposed scheme explores only a small number of candidate sequences in the first subsystem; thus, it achieves significant complexity reduction. Two new candidate sequence selection methods are proposed. In the first iteration, the candidate sequences used for PIC are selected by exploring the statistical properties of the received signals. In the second iteration and beyond, the set containing the candidate sequences is constructed by utilizing the soft information generated from the previous iteration. The proposed scheme provides a balanced tradeoff between computational complexity and bit error rate (BER) performance. [ABSTRACT FROM PUBLISHER]

Distributed antenna systems (DASs) and FemtoCells (FCs) are capable of improving the attainable performance in the cell-edge area and in indoor residential areas, respectively. To achieve high spectral efficiency (SE), both the distributed antenna elements (DAEs) and FC base stations (FBSs) may have to reuse the spectrum of the macrocellular network. As a result, the performance of both outdoor MacroCell (MC) users (OMU) and indoor FC users (IFUs) suffers from CoChannel Interference (CCI). Hence, in this paper, heterogenous cellular networks are investigated, where the DAS-aided MCs and FCs coexist within the same area. Both the outage probability (OP) and the spatially averaged throughput are derived, and the network is optimized either to minimize the OP or to maximize the MC's throughput. Our analysis demonstrates that surprisingly, the unity frequency-reuse (UFR)-based macrocellular system can be optimized in isolation, without considering the impact of FCs. We found that the MCs relying on fractional frequency reuse (FFR) tend to be converted to several small cells, illuminated by the DAEs, when the density of FCs becomes high. [ABSTRACT FROM PUBLISHER]

A gradient-based method is designed for power allocation in orthogonal-frequency-division-multiplexing (OFDM) -based cognitive radio networks. The resource allocation problem subject to a mutual interference constraint is considered. We utilize the gradient descent approach to allocate power to subcarriers in cognitive radio (CR) networks. The proposed gradient-based power allocation method with a well-designed step size can approximate the optimal solution within a few iterations. Due to the derived equation for power allocation in an adaptive manner, the proposed method is feasible for adaptive power allocation in time-varying channels. The analysis for the selection of the step size is presented in this paper. For comparison purposes, a greedy power-loading method requiring numerous iterations is also designed for this power allocation problem. The proposed gradient-based method and the greedy power-loading method both have a computational complexity of O(N), but the proposed gradient-based method requires far fewer iterations. As demonstrated in the simulation results, the proposed gradient-based method with the adaptive step size has a fast rate to achieve a near-optimal solution within an extremely small number of iterations and has quite a low computational complexity of O(N). [ABSTRACT FROM PUBLISHER]

Cooperative communications has received tremendous interests in wireless systems. The communication performance of a single source–destination pair can be enhanced via the help of relays in traditional cooperative communications. Recent advances in interference cancelation (IC) can further enhance the performance of parallel cooperative transmissions between multiple source–destination pairs. Although some works have been done on cooperative communications, most existing works are focused on link-level physical-layer issues. Consequently, the potential benefits of cooperative communications on network-level upper layer issues, such as topology control, are largely ignored in existing works. In this paper, we study the impacts of cooperative communications, particularly IC-based cooperative communications, on topology control in wireless ad hoc networks (WANETs). We propose a distributed cooperative topology control scheme with opportunistic IC (COIC) to improve network capacity in WANETs by jointly considering both upper layer network capacity and physical-layer cooperative communications with IC. We show that the benefits brought by cooperative communications are opportunistic, which rely on network structures and channel conditions. These opportunistic advantages have significant impacts on network capacity, and our proposed COIC can effectively capture these opportunities to substantially improve network capacity. [ABSTRACT FROM PUBLISHER]

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]

In this paper, we study the energy efficiency (EE) of a downlink multicell massive distributed antenna system (DAS) in the presence of pilot contamination (PC), where the antennas are clustered on the remote radio heads (RRHs). We employ a practical power consumption model by considering the transmit power, the circuit power, and the backhaul power, in contrast to most of the existing works which focus on colocated antenna systems (CASs), where the backhaul power is negligible. For a given average user rate, we consider the problem of maximizing the EE with respect to the number of antennas of each RRH $n$, the number of RRHs $M$, and the number of users $K$ and study the impact of system parameters on the optimal $n$, $M$, and $K$. Specifically, by applying random matrix theory, we derive the closed-form expressions of the optimal $n$ and find the solution of the optimal $M$ and $K$ under a simplified channel model with maximum ratio transmission. From the results, we find that, to achieve the optimal EE, a large number of antennas is needed for a given user rate and PC. As the number of users increases, EE can be improved further by having more RRHs and antennas. Moreover, if the backhauling power is not large, a massive DAS can be more energy efficient than a massive CAS. These insights provide a useful guide to the practical deployment of massive DASs. [ABSTRACT FROM PUBLISHER]

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]

To improve the efficiency of wireless data communications, new physical-layer transmission methods based on known-interference cancelation (KIC) have been developed. These methods share the common idea that interference can be canceled when its content is known. Existing work on KIC mainly focuses on single-hop or two-hop networks, with physical-layer network coding and full-duplex communications as typical examples. This paper extends the idea of KIC to general multihop networks and proposes an end-to-end KIC (E2E-KIC) transmission method, together with its medium access control (MAC) design. With E2E-KIC, multiple nodes in a flow passing through a few nodes in an arbitrary topology can simultaneously transmit and receive on the same channel. We first present a theoretical analysis on the effectiveness of E2E-KIC in an idealized case. Then, to support E2E-KIC in multihop networks with an arbitrary topology, we propose an E2E-KIC-supported MAC protocol (E2E-KIC MAC), which is based on an extension of the Request-to-Send/Clear-to-Send mechanism in the IEEE 802.11 MAC. We also analytically analyze the performance of the proposed E2E-KIC MAC in the presence of hidden terminals. Simulation results illustrate that the proposed E2E-KIC MAC can improve network throughput and reduce end-to-end delay. [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]

In this paper, we propose an interference alignment (IA) scheme in which the performance of the secondary users (SUs) transmitting their information on the same frequency band of the preexisting primary links is improved in terms of achievable sum rate without generating interference on the primary network. In our scenario, in which the primary users (PUs) are cooperating through IA and a set of SUs joins the network, we propose an efficient approach to find the values of the preprocessing and postprocessing filters of these SUs. Moreover, the SUs must not receive/generate any interference from/to the PUs. To preserve the primary network from the interference caused by the SUs, we also employ a method in which the distance between the subspace of the received signal from each secondary transmitter at the PUs and the set of interference subspaces at the primary links is minimized. In result, we would tackle with a computationally hard optimization problem with the sum rate of the secondary links as the objective function. We present the solutions in the cases where one or two SUs join the network. In situations where more SUs join the network simultaneously, we may apply other levels of IA between the secondary links after suppressing the mutual interference between the primary and secondary networks. The analytical results are confirmed through simulations. [ABSTRACT FROM PUBLISHER]

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, there has been strong interest in exploiting advanced physical-layer techniques to increase the capacity of multihop wireless networks. Several recent studies have emerged with a particular focus on successive interference cancelation (SIC) as an effective approach to allow multiple adjacent concurrent transmissions to coexist, enabling multipacket reception. This paper is in line with those efforts in that we attempt to understand the benefits of SIC on the throughput performance of wireless networks. We consider a cross-layer design for the joint congestion control, routing, and scheduling problem in wireless networks where nodes are endowed with SIC capabilities and under the general physical signal-to-interference-plus-noise ratio (SINR) interference model. We use duality theory to decompose the joint design problem into congestion control and routing/scheduling subproblems, which interact through congestion prices. This decomposition enables us to solve the joint cross-layer design problem in a completely distributed manner. Given that the problem of scheduling with SIC and under the SINR interference regime is NP-hard, this paper develops a decentralized approach that allows links to coordinate their transmissions and, therefore, efficiently solve the link scheduling problem. Numerically, we show that our decentralized algorithm achieves similar results to those obtained by other centralized methods (e.g., greedy maximal scheduling). We also study the performance gains SIC brings to wireless networks, and we show that flows in the network achieve up to twice their rates in most instances, in comparison with networks without interference cancelation capabilities. These gains are attributed to the capabilities of SIC to better manage the interference and promote higher spatial reuse in the network. [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]