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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]

This paper concerns the uplink of multicell multiuser multiple-input multiple-output (MIMO) systems. To tackle the effect of pilot contamination that is generally viewed as a bottleneck in previous work, this paper presents a superimposed pilot (SP)-aided uplink channel estimation scheme and mathematically characterizes the impact that an SP has on the performance of such a very large MIMO system. It is shown that there are two types of interference components that do not vanish, even when the number of antennas $M$ grows to infinity. The first type, which is referred to as cross-contamination, is due to the correlation between the SP and data among different cells. The second type, which is referred to as self-contamination, is due to the dependence between channel estimation and estimation error. Cross-contamination is, in principle, similar to pilot contamination in a conventional pilot-based multicell MIMO system, whereas self-contamination is unique for the SP-aided scheme. Both theoretical and simulation results demonstrate that the SP-aided scheme can effectively reduce the estimation contamination by increasing the data frame size and, in turn, achieve a significant improvement over the spectral efficiency, in comparison with conventional pilot-based methods. [ABSTRACT FROM AUTHOR]

In this paper, we propose a channel transformation technique for joint decoding of desired and interfering signals in an interference alignment scenario consisting of $K$ users with multiple antennas. Our technique, i.e., pseudo-lattice treatment, is based on the compute-and-forward framework. Our technique can be implemented to provide decoding gains with low complexity for subspace aligned interference signals. We evaluate the performance of the system through simulations that show the performance gain attained by using our pseudo-lattice method over subspace decoding techniques for interference alignment in low- and medium-SNR conditions. [ABSTRACT FROM AUTHOR]

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]

Coordinated multipoint joint transmission (JT) is a vital technique of the fifth-generation (5G) networks to increase throughput but causes a significant burden on network backhaul because the same user data must distribute to multiple base stations, called a JT cluster. Thus, many studies have explored how to reduce backhaul data traffic using caching user data at base stations. Millimeter wave (mmWave) mesh backhaul is a promising architecture for small cells to exchange cache data over 5G networks. However, this paper observes that inappropriate JT clusters and routing paths will result in unnecessary mmWave mesh backhaul bandwidth consumption such that the performance gain of the JT will be reduced. Therefore, in this paper, we study the JT clustering problem with the consideration of caches at base stations and mmWave mesh backhaul. The objective is to minimize total backhaul traffic while satisfying the data rate requirement of each user under limited radio resource units. We propose a two-stage algorithm based on dynamic programming approach to solve the problem. We prove that the dynamic programming algorithm can find an optimal solution for our subproblem. The simulation results provide several insights and show that compared with two baseline algorithms, our proposed algorithm can significantly reduce more backhaul bandwidth consumption. [ABSTRACT FROM AUTHOR]

In this paper, a new transmission scheme, signal space cognitive cooperation, is introduced by applying the idea of signal space diversity in an underlay spectrum sharing decode-and-forward multirelay cooperative network. In the proposed structure, the secondary source signal is rotated by a certain angle and then the source and the secondary best relay transmit the in-phase and the quadrature components of the rotated signal. As a consequence, two source signals, rather than one, are transmitted in two-time slots which improves data rates considerably, compared to the conventional cognitive cooperative schemes. In this paper, proactive relaying mode is used in which the best relay is selected based on the max–min selection criterion before executing the transmission. Considering both statistical and the instantaneous channel state information of the feedback channel between the primary receiver and the secondary network, two power allocation methods are adopted at the source. For both methods, closed-form expressions of error probability are derived. Moreover, asymptotic analysis is performed and diversity gain is obtained to provide further insights about the system performance. Finally, analytical expressions are verified by Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

In this paper, we consider a general centralized feedback model for interference alignment (IA) algorithms of which precoders and decoders are designed with quantized channel state information (CSI) at a central unit and then fed back to corresponding transmitters and receivers via finite-rate links. The significant difference of this model from existing models is that all the realizations of channels, precoders, and decoders are fed back by finite rates. The signal-to-interference-plus-noise ratio (SINR) characteristic of this model is analyzed, which helps derive an upper bound of average throughput loss relative to perfect IA. The upper bound is shown to be tight by simulation, particularly in the high-feedback regime. Based on this result, the scaling laws of feedback bits for channels, precoding, and decoding vectors to obtain full degree of freedom are derived, which are backward compatible to the existing results for quantized CSI only or quantized precoder only. Simulation results show that the system is interference limited at a high signal-to-noise ratio (SNR) if the three scaling laws are not simultaneously satisfied, and the throughput performance is dominantly limited by the worst feedback links among the channels, precoders, and decoders. [ABSTRACT FROM PUBLISHER]

In this paper, we consider nonregenerative multipair two-way relaying systems, where a relay node supports $K$ pairs of two-way communications in the presence of imperfect channel state information (CSI). We employ a stochastic approach to model the channel uncertainties and study a robust beamforming design at the relay. It is shown that the proposed beamformer provides a reduction in the computational complexity, as well as good robustness against channel errors, compared with conventional designs. To reduce the estimation overhead at the users, we also suggest an efficient downlink training method to inform the users of the channel-dependent self-interference cancellation (SIC) parameters. With the training method, the additive noise may incur a malfunction of the SIC. To address this issue, we develop an intelligent selection criterion that decides whether the SIC should be adopted or not. Finally, from simulation results, we demonstrate the efficiency of our proposed schemes. [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]

Multicell coordinated beamforming (CB) can mitigate intercell interference (ICI). However, existing work on CB focuses on systems that maximize overall throughput. This paper considers CB for systems with multiple receive antennas and further extends the CB to multiuser and multistream transmission. We consider fairness and pay close attention to cell-edge users. CB that maximizes the harmonic sum of signal-to-interference-plus-noise ratio (SINR) can be derived into a low-complexity algorithm that favors cell-edge users. Two iterative algorithms are developed. From the simulation results, the proposed algorithms can provide a better fifth-percentile user throughput compared with the CB algorithms minimizing mean square error, maximizing uplink SINR, and maximizing weighted sum rate. Furthermore, the computational complexity of the proposed algorithms is significantly lower than that maximizing the minimum SINR of users. [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]

Device-to-device (D2D) communication plays a crucial role in improving the performance of cellular systems, and it is expected to be an innovative technology for next-generation wireless systems. Although significant progress has been made toward cellular and D2D coexistence, the issue of access control for D2D communications in the cellular network has received limited attention. In this paper, we address this issue by employing the network calculus (NC) theory for the first time. We propose a multipriority model, which assigns the strictly highest priority to cellular users and multiple levels of priority to D2D users to characterize the communication requests' access. The proposed model facilitates interference avoidance between cellular and D2D communications and, thus, enhances the quality of service (QoS) of the cellular system. We also apply the NC theory to analyze the worst-case performance of service rate, delay, and backlog for processing communication requests of cellular and D2D users. Both theoretical and experimental results demonstrate that the proposed model is effective and applicable to characterize the access control for D2D communications underlaying cellular networks. [ABSTRACT FROM AUTHOR]

In this paper, we study user selection (US) strategies for a multiple-input–multiple-output (MIMO) cognitive radio (CR) downlink network, where the r-antenna underlay CR secondary users (SUs) coexist with a primary user (PU), and all terminals are equipped with multiple antennas. Two main scenarios are considered: 1) The t-antenna cognitive base station (CBS) has perfect or partial channel state information at the transmitter (CSIT) from the CBS to the PU receiver (RX), and 2) the CBS has absolutely no PU CSIT. For these scenarios, we propose and evaluate multiple SU selection schemes that are applicable to both best-effort PU interference mitigation and hard interference temperature (IT) constraints. The computational complexity of the proposed schemes can be significantly smaller than that of an exhaustive search with negligible performance degradation. For the selection of C SUs out of K, whereas an exhaustive search is on the order of \mathcal{O}(\binom{K}{C}C^4r^3). When t$ and r$ are of the same order, the computational complexity of the proposed scheme can be \binom{K}{C}C^4/K times smaller. Mathematical complexity analysis and numerical simulations are provided to show the advantage of our schemes. [ABSTRACT FROM PUBLISHER]

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]

Coordinated tethering over a white-space spectrum is investigated herein to increase mobile broadband spectrum efficiency in densely populated areas. This paper proposes an algorithm for operator-controlled tethering over white spaces. The proposed approach does not add to the existing infrastructure but instead allows the individual nodes to act as “hotspots” and to tether data to and from other nodes. The proposed algorithm iteratively clusters the nodes into hotspots and slaves and allocates resources to maximize spectrum utility. The proposed method's dynamic characteristics allow cellular systems to hierarchically evolve in dense areas as necessary. A signaling framework for node-to-node and base-station-to-node communication that enables such operator-controlled tethering is also presented. Simulation results show that given a fixed amount of network resources, the proposed algorithm can significantly increase the number of supported users. [ABSTRACT FROM PUBLISHER]

A fundamental challenge in orthogonal-frequency-division-multiple-access (OFDMA)-based cellular networks is intercell interference coordination, and to meet this challenge, various solutions using fractional frequency reuse (FFR) have been proposed in the literature. However, most of these schemes are either static in nature, dynamic on a large time scale, or require frequent reconfiguration for event-driven changes in the environment. The significant operational cost involved can be minimized with the added functionality that self-organizing networks bring. In this paper, we propose a solution based on the center of gravity of users in each sector. This enables us to have a distributed and adaptive solution for interference coordination. We further enhance our adaptive distributed FFR scheme by employing cellular automata as a step toward achieving an emergent self-organized solution. Our proposed scheme achieves a close performance with strict FFR and better performance than SFR in terms of the edge user's sum rate. [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]

Enhanced intercell interference coordination (eICIC) is known to provide promising performance benefits for Long-Term Evolution Advanced heterogeneous networks (LTE-Advanced HetNets). The use of eICIC facilitates more flexible interlayer load balancing by means of small-cell range extension (RE) and almost blank subframes (ABSs). Although the eICIC configuration (RE and ABS) ideally should be instantaneously adapted to follow the fluctuations of the traffic and the channel conditions over time, previous studies have focused on slow intercell coordination. In this paper, we investigate fast-dynamic eICIC solutions for centralized and distributed radio resource management (RRM) architectures. The centralized RRM architecture assumes macrocells and remote radio heads (RRHs) interconnected via high-speed fronthaul connections, whereas the distributed architecture is based on traditional macrocell and picocell deployments with an X2 backhaul interface. Two different fast muting adaptation algorithms are derived, and it is shown how those can be applied to both the centralized and distributed architectures. Performance results with bursty traffic show that the fast-dynamic adaptation provides significant gains, both in fifth-percentile and 50th-percentile user throughputs, and improvements in user fairness. The best performance is naturally obtained for the centralized architecture, although the performance of the distributed architecture is comparable for the cases where enhanced X2 intercell information exchange is exploited. [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]

With interference alignment (IA), the achievable degrees of freedom (DoFs) in wireless networks can be linearly scaled up with the number of users. However, to attain the full DoF, the availability of perfect network channel state information (CSI) is mandatory, which is not pragmatic in general. In this paper, we quantify the performance of IA under CSI mismatch where the variance of the CSI measurement error depends on the signal-to-noise ratio (SNR). We show that when this error variance is proportional to the inverse of the SNR, the full DoF is achievable, and an upper bound on asymptotic mean loss in sum rate compared with the perfect CSI case is derived. We also derive a bound on the achievable DoF when the CSI error variance is proportional to the inverse of the SNR to a power of a constant. Furthermore, we investigate the effect of CSI mismatch on the performance of the maximum signal-to-interference-plus-noise ratio (Max-SINR) algorithm. We show that with perfect CSI, the Max-SINR algorithm outperforms interference leakage minimization algorithms, but with the presence of imperfect CSI, its comparative improvement becomes negligible. We then propose an adaptive Max-SINR algorithm that can notably improve the performance of the original Max-SINR algorithm under CSI mismatch. [ABSTRACT FROM AUTHOR]

We consider the joint subchannel allocation and power control problem for orthogonal frequency-division multiple-access (OFDMA) femtocell networks in this paper. Specifically, we are interested in the fair resource-sharing solution for users in each femtocell that maximizes the total minimum spectral efficiency of all femtocells subject to protection constraints for the prioritized macro users. Toward this end, we present the mathematical formulation for the uplink resource-allocation problem and propose an optimal exhaustive search algorithm. Given the exponential complexity of the optimal algorithm, we develop a distributed and low-complexity algorithm to find an efficient solution for the problem. We prove that the proposed algorithm converges and we analyze its complexity. Then, we extend the proposed algorithm in three different directions, namely, downlink context, resource allocation with rate adaption for femto users, and consideration of a hybrid access strategy where some macro users are allowed to connect with nearby femto base stations (FBSs) to improve the performance of the femto tier. Finally, numerical results are presented to demonstrate the desirable performance of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

This paper proposes a reduced-complexity multichannel assignment scheme for short-range cellular systems. It treats the scenario when a number of small-cell (e.g., femtocell) access points (APs) can be shared to serve active scheduled users. The APs employ isotropic antenna arrays and operate using an open-access control strategy. To improve the reuse ratio of physical resources, the APs are assumed to occupy a single physical channel, wherein coordination among them is infeasible. On the other hand, to improve the spatial coverage, a scheduled user can be served by a single transmit channel from an AP at a time. For the case of overloaded APs and when the feedback links are capacity limited, the scheme attempts to identify the suitable transmit channels from the deployed APs in an adaptive manner such that certain performance and/or processing load limits are satisfied. The effects of some system and design parameters on the outcomes of the scheme are thoroughly discussed. Novel results for the statistics of the resulting interference power are presented, from which results for some performance measures and processing loads are obtained. Numerical and simulations results are provided to clarify the achieved gains, as compared with related models under different operating conditions. [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]

Heterogeneous networking is a promising solution for improving wireless coverage, relieving overcrowded bandwidth, and enhancing system throughput for next-generation wireless networks. However, one of the main concerns to put through heterogeneous networks is the interference among overlaid cells. In this paper, we consider femtocell uplink transmissions with dynamic and short-period interference (also called shot interference) from macrocell users. It is shown that, without the information on interferer channels between femtocells and macrocells at any base station, femtocell networks suffer from severe performance degradation when they adopt orthogonal frequency-division multiple access (OFDMA) or single-carrier FDMA (SC-FDMA) techniques. To mitigate the stringent shot interference, we propose a precoded FDMA (P-FDMA) transmission with novel detectors. Our results show that the proposed designs collect multipath diversity in the presence of interference without the knowledge of interferer channels, and our designs are robust to the power levels of shot interference. Simulation results validate our theoretical findings. [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]

When a large number of machine-to-machine (M2M) terminals attempt to access the Long-Term Evolution (LTE)/LTE Advanced (LTE-A) cellular network using the physical random access channel (PRACH), congestion and overload may result, which can lead to serious degradation of performance for both M2M and human-to-human (H2H) terminals. The main cause for this is the inherent complexity of the four-way handshake used for random access, which is well suited for H2H terminal access but unsuitable for massive M2M access. In this paper, we describe an efficient scheme for concurrent M2M and H2H access on the PRACH, which separates the resources for M2M and H2H access at the level of preamble codes and avoids the use of the four-step handshake for M2M terminals by implementing a carrier sense multiple access with collision avoidance (CSMA/CA) overlay network using the designated preamble codes. We analyze the performance of the scheme for both H2H and M2M traffic and show the values of the most important design parameters that enable this scheme to support concurrent access by H2H and M2M terminals with little performance degradation. [ABSTRACT FROM PUBLISHER]

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]

This paper investigates the benefits of incorporating full-duplex (FD) into an underlaid device-to-device (D2D) cellular network via centralized and distributed power control mechanisms. In the considered system, D2D users operate in an FD mode under the adverse effect of realistic residual self-interference, and their locations are modeled by a homogeneous spatial Poisson point process. By first considering a centralized power control scheme, we first formulate an optimization problem that maximizes the D2D link sum-rate under the constraint on minimum target signal-to-interference-plus-noise ratio (SINR) at each user. Since the problem is nonconvex, we propose a difference of convex based method to transform the problem into a sequence of convex subproblems which can be solved efficiently. The obtained solutions help to calculate the coverage probability of both cellular and D2D links, showing that a very high coverage probability of cellular link can be achieved while successfully supporting a large number of active D2D links. In the second part of the paper, we consider a distributed power control scheme where only the local channel state information of direct link between respective D2D users is needed. By utilizing the tools of stochastic geometry, we derive closed-form approximations of coverage probabilities for both cellular and D2D links. Specifically, we apply Laplace transforms and novel approximations that accurately approximate the expected values of fractional and exponential functions of random variables to obtain the distribution functions of SINRs at the base-station and D2D users in a closed form. By further taking the average over the distributions of cellular and D2D link distances, we then arrive at the closed-form approximations of cellular and D2D coverage probabilities. In addition, based on the approximation of D2D link coverage probability, an analytical expression for the D2D link sum-rate is also obtained, and it can be effectively calculated. [ABSTRACT FROM AUTHOR]

This paper examines the impact of multiple requests based user association model on the performance of ultra-dense small cell network. We consider a cache-enabled small cell network where popular files are cached in different small cells according to the spatial popularity of files. Unlike traditional models, where a user sends requests to a single nearby small cell, we propose a multi-request based user association model (MRAM). In this model, a user selects multiple small cells in its vicinity, referred to as neighbors, for sending file requests. This subset of neighbors search the requested file simultaneously, in order to provide it to the user at the small cell level. This results in an improved coverage probability, which increases the cache hit ratio, eventually alleviating the backhaul congestion. We further exploit coverage probability by considering different coverage patterns and derive closed-form expressions based on these coverage scenarios. We concretely demonstrate that the performance of such a multi-request model is improved with user's movement in different regions. Gains obtained from MRAM are quantified in terms of coverage probability through numerical simulations as well as network simulations. [ABSTRACT FROM AUTHOR]

In this paper, a cocktail approach is proposed to delicately integrate the two conventional countermeasures, i.e., the fractional pilot reuse and time-shifted pilots (TSP) schemes, for the pilot contamination problem in the full-duplex massive multiple-input multiple-output system. Specifically, the TSP scheme is applied to duplicate for the inner and edge regions of a cell such that the number of accommodated users can be doubled. To achieve this, the base station should operate in the full-duplex mode; also, the pilot symbols rather than the pilot sequences are used to attain the user diversity gain. The simulation results verify the accuracy of the numerical analysis and the remarkably boosted sum rate for both the downlink and uplink cases. [ABSTRACT FROM AUTHOR]

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 multi-user multi-cell multiple-input multiple-output (MIMO) visible light communication (VLC) systems, inter-cell interference (ICI) and inter-user interference (IUI) are the two key factors that could severely degrade the system performance. In this paper, for the first time, a novel joint precoder and equalizer design based on interference alignment is proposed to mitigate both IUI and ICI in multi-user multi-cell MIMO VLC systems under imperfect channel state information (CSI). The proposed approach aims to choose proper precoder and receiving equalizer to minimize the mean square error (MSE) under the unique optical power constraints in VLC. Furthermore, we consider optical channel estimation error in our formulated joint optimization problem when designing the joint precoder and receiving equalizer in multi-user multi-cell MIMO VLC systems. Numerical results show that the proposed design achieves a better performance under different users locations, channel estimation errors, and transmitter/receiver spacing, compared to the existing minimum mean square error (MMSE) and max-rate designs. Especially, when the transmit optical power is 12 W per light emitting diode (LED) lamp, our proposed design achieves a sum rate improvement of up to 18.2% and 28.7% as compared with the MMSE and max-rate designs, respectively. In addition, the proposed design can save about 1.4 and 4.3 W optical power per LED lamp as compared with the MMSE and max-rate designs, respectively, at a target bit error rate (BER) of 10 $^{-3}$. [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]

In this correspondence paper, we design a massive nonorthogonal multiple access (NOMA) scheme with delay provisioning for cellular internet-of-things. In the context of massive access, the severe interuser interference decreases the quality of the received signal, such that it is a nontrivial task to provide a delay provisioning for heterogeneous wireless services. To solve this challenge, we propose a massive NOMA scheme to meet the delay requirements of a large number of users by exploiting the properties of rateless codes. Especially, we present a power allocation algorithm to minimize the power consumption while achieving delay-constrained massive access. Finally, simulation results validate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper studies the degrees of freedom (DoF) of two-way $2\times 2\times 2$ MIMO interference networks, a class of two-way four-unicast networks. We first provide upper and lower bounds on the sum DoF of general two-way $2\times 2\times 2$ MIMO interference networks with any number of antennas in each node. We then investigate the special case where all user nodes have $M$ antennas and relay nodes have $N$ antennas, and provide the simplified bounds on the sum DoF. We show that our proposed achievable rate for this special case is higher than the achievable rates recently proposed in. Moreover, for this special case, we obtain the exact DoF $=4M$ when $N \geq 2M$ , and DoF $=4N$ when $M \leq 2N$. [ABSTRACT FROM AUTHOR]

Cellular networks are increasingly densified to deal with the fast growing wireless traffic. Interference mitigation plays a key role for the dense cellular networks. Successive interference cancellation (SIC) and fractional frequency reuse (FFR) are two representative inter-cell interference (ICI) mitigation techniques. In this paper, we study the application of both SIC and FFR for LTE uplink networks, and develop an analytical model to investigate their interactions and impact on network performance. The performance gains with FFR and SIC are related to key system functionalities and variables, such as SIC parameters, FFR bandwidth partition, uplink power control and sector antennas. The ICIs from individual cell sectors are approximated by log-normal random variables, which enables low complexity computation of the aggregate ICI with FFR and SIC. Then, network performance of site throughput and outage probability is computed. The model is fast and has small modeling deviation, which is validated by simulations. Numerical results show that both SIC and FFR can largely improve network performance, but SIC has a stronger impact than FFR. In addition, most of the network performance gains with SIC could be obtained with a small number of SIC stages applied to a few sectors. [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]

Device-to-device (D2D) communication has been recently proposed to reduce cellular traffic by directly connecting the local nodes. In this paper, we consider a cellular-based primary network coexisting with a cognitive D2D pair. The primary network consists of a base station and multiple cellular users, which can sell their spectrum to the D2D user. Additionally, under low-interference conditions, the spectrum can be simultaneously shared between cellular users and D2D-capable users, which is called the nonorthogonal sharing mode. We introduce a double-sided bandwidth-auction game for cognitive D2D communication. In the auction, the D2D transmitter has three types of service providers (SPs) or sharing modes. The SPs operate on different frequency spectra, and a D2D-capable pair intends to share these spectra. This situation is formulated as an auction game, where a D2D transmitter bids a demand price–bandwidth curve, and each SP offers a price–bandwidth supply curve. The Nash equilibrium point of the auction game is analytically obtained. Then, a learning method is proposed for the decision making of the players in an incomplete-information repeated game. Moreover, the convergence of the proposed learning method to the Nash equilibrium point is studied through the converse Lyapunov theorem. Finally, the proposed auction game is extended to the multiple-D2D case, and the optimal bandwidth allocation strategy to maximize the sum rate is derived. [ABSTRACT FROM PUBLISHER]

This paper considers the resource allocation for an orthogonal-frequency-division-multiplexing (OFDM)-based cognitive decode-and-forward (DF) relay network. Our objective is to maximize the sum rate (over subcarriers) of the cognitive-radio user with the interference introduced to the primary users (PUs) being managed. The optimization is over subcarrier pairing and power allocation, which leads to a mixed-integer programming (MIP) problem. To resolve this complicated MIP problem at a reasonable cost, we adopt the heterogeneous genetic algorithm (HGA) framework. The main motivation for the HGA framework comes from the idea that it can reduce the impact of extra assumptions made in previous works to simplify the problem. In our HGA, the chromosome is divided into an integer string for subcarrier pairing and a real-number string for power allocation. Two new initialization methods of these chromosomes, which are motivated by the convex optimization theory, are proposed. New crossover and mutation schemes are also devised to accommodate these new chromosomes, as well as to manage the interference to the PUs. Furthermore, we also propose a two-stage low-complexity genetic algorithm, which separately determines the proper subcarrier pairs and power allocations. Our simulations show that our HGAs and the two-stage algorithm provide competing performance, compared with similar state-of-the-art works. [ABSTRACT FROM PUBLISHER]

Very recently, regulatory bodies worldwide have approved dynamic access of unlicensed networks to the TV white space (TVWS) spectrum. Hence, in the near future, multiple heterogeneous and independently operated unlicensed networks will coexist within the same geographical area over shared TVWS. Although heterogeneity and coexistence are not unique to TVWS scenarios, their distinctive characteristics pose new and challenging issues. In this paper, the problem of the coexistence interference among multiple heterogeneous and independently operated secondary networks (SNs) in the absence of secondary cooperation is addressed. Specifically, the optimal coexistence strategy, which adaptively and autonomously selects the channel maximizing the expected throughput in the presence of coexistence interference, is designed. More in detail, at first, an analytical framework is developed to model the channel selection process for an arbitrary SN as a decision process. Then, the problem of the optimal channel selection, i.e., the channel maximizing the expected throughput, is proved to be computationally prohibitive (NP-hard). Finally, under the reasonable assumption of identically distributed interference on the available channels, the optimal channel selection problem is proved not to be NP-hard, and a computationally efficient (polynomial-time) algorithm for finding the optimal strategy is designed. Numerical simulations validate the theoretical analysis. [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]

Nonorthogonal multiple access (NOMA) represents a paradigm shift from conventional orthogonal multiple-access (MA) concepts and has been recognized as one of the key enabling technologies for fifth-generation mobile networks. In this paper, the impact of user pairing on the performance of two NOMA systems, i.e., NOMA with fixed power allocation (F-NOMA) and cognitive-radio-inspired NOMA (CR-NOMA), is characterized. For F-NOMA, both analytical and numerical results are provided to demonstrate that F-NOMA can offer a larger sum rate than orthogonal MA, and the performance gain of F-NOMA over conventional MA can be further enlarged by selecting users whose channel conditions are more distinctive. For CR-NOMA, the quality of service (QoS) for users with poorer channel conditions can be guaranteed since the transmit power allocated to other users is constrained following the concept of cognitive radio networks. Because of this constraint, CR-NOMA exhibits a different behavior compared with F-NOMA. For example, for the user with the best channel condition, CR-NOMA prefers to pair it with the user with the second best channel condition, whereas the user with the worst channel condition is preferred by F-NOMA. [ABSTRACT FROM AUTHOR]

In device-to-device (D2D) communications, channel state information (CSI) is exploited to manage the interference between D2D users and regular cellular users (CUs) and improve system performance. However, obtaining the accurate CSI is usually difficult and causes high overhead, particularly when the links are not connected to the base station (BS), such as the links between regular CUs and D2D receivers (CU-D links). In this paper, we investigate the signaling overhead and performance tradeoff in D2D communications with channel uncertainty. To limit interference to regular CUs, we only allow the resource of a CU to be reused by, at most, one D2D pair. We also assume that only partial CSI of the CU-D links is available at the BS and develop two different strategies to deal with the channel uncertainty, namely, probabilistic and partial feedback schemes. We first derive a probability-based resource-allocation scheme by utilizing channel statistical characteristics to maximize the overall throughput of the CUs and admissible D2D pairs while guaranteeing their quality of service (QoS) in terms of signal-to-interference-plus-noise ratio (SINR) and outage probability, respectively. Then, we propose an efficient feedback scheme to reduce the overhead of CSI feedback while providing near-optimal performance. In addition, we propose a combined scheme to take advantages of both probabilistic and partial feedback schemes. It is shown by simulation that there exists an optimal threshold of the outage probability for probabilistic scheme while the partial feedback scheme is robust to the channel models. Furthermore, the combined scheme outperforms the probabilistic and the partial feedback schemes in terms of overall throughput. [ABSTRACT FROM PUBLISHER]

Low-complexity linear precoders are known to be close to optimal for massive multiple-input multiple-output (M-MIMO) systems. However, the large number of antennas at the transmitter imposes a high computational burden and high hardware overloads. In line with this, in this paper, we propose a low-complexity antenna selection (AS) scheme that selects the antennas that maximize constructive interference between the users. Our analyses show that the proposed AS algorithm, in combination with a simple matched-filter (MF) precoder at the transmitter, is able to achieve better performances than systems equipped with a more complex channel inversion (CI) precoder and computationally expensive AS techniques. First, we give an analytical definition of constructive and destructive interference, based on the phase of the received signals from phase-shift-keying-modulated transmissions. Then, we introduce the proposed AS algorithm, which identifies the antenna subset with the highest constructive interference, maximizing the power received by the user. In our study, we derive the computational burden of the proposed technique with a rigorous and thorough analysis, and we identify a closed-form expression of the upper bound received power at the user side. In addition, we evaluate in detail the power benefits of the proposed transmission scheme by defining an efficiency metric based on the achieved throughput. The results presented in this paper prove that AS and green radio concepts can be jointly used for power-efficient M-MIMO, as they lead to significant power savings and complexity reductions. [ABSTRACT FROM AUTHOR]

To meet the demand of increasing mobile data traffic and provide better user experience, heterogeneous cellular networks (HCNs) have become a promising solution to improve both the system capacity and coverage. However, due to dense self-deployment of small cells in a limited area, serious interference from nearby base stations may occur, which results in severe performance degradation. To mitigate downlink interference and utilize spectrum resources more efficiently, we present a novel graph-based resource allocation and interference management approach in this paper. First, we divide small cells into cell clusters, considering their neighborhood relationships in the scenario. Then, we develop another graph clustering scheme to group user equipment (UE) in each cell cluster into UE clusters with minimum intracluster interference. Finally, we utilize a proportional fairness scheduling scheme to assign subchannels to each UE cluster and allocate power using water-filling method. To show the efficacy and effectiveness of our proposed approach, we propose a dual-based approach to search for optimal solutions as the baseline for comparisons. Furthermore, we compare the graph-based approach with the state of the art and a distributed approach without interference coordination. The simulation results show that our graph-based approach reaches more than 90% of the optimal performance and achieves a significant improvement in spectral efficiency compared with the state of the art and the distributed approach both under cochannel and orthogonal deployments. Moreover, the proposed graph-based approach has low computation complexity, making it feasible for real-time implementation. [ABSTRACT FROM AUTHOR]