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Non-orthogonal multiple access (NOMA) is increasingly becoming very attractive in cloud radio access networks (CRANs) to further boost the overall spectral efficiency, connectivity and, capacity of such networks. This paper addresses optimizing the energy efficiency (EE) for the downlink of a NOMA-based two tiers CRAN. The stochastic geometry represented by Poisson Point Process (PPP) distribution is used to decide the number and locations of the base stations (BSs) in each tier within the coverage area. A numerical optimal solution is obtained and compared against a proposed subgradient solution, as well as another proposed unoptimized solution based on the false positioning method. For comparison purposes, two other power allocation techniques are presented to allocate different powers to various BS categories; one allocates the power to each BS based on their relative distances to the cloud-based central station and the other is the bisection based scheme. Two simulation scenarios are presented to examine the performance of the two-tier NOMA-CRANs with NOMA is adopted as the multiple access of each tier in both cases. The first scenario considers heterogeneous CRAN (NOMA-HCRAN) case by using two different BS categories in each tier, namely, the macro-BSs and the RRHs. The second scenario considers a homogeneous CRAN (NOMA-CRAN) case by using the RRHs in both tiers but each tier has different frequency layer to prevent cross tier interference. Simulation results show the promising performance gain can be achieved with the proposed techniques relative to the existing approaches. More specifically, it was illustrated that the proposed subgradient based NOMA CRAN offers better performance than the proposed false positioning based NOMA CRAN, which is in turn better than the existing techniques, in particular, the bisection and the distance based NOMA-CRAN. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) is considered as a promising technology, which can effectively control the phase of signals with low-cost reflective elements. In this paper, we investigate the RIS-assisted D2D communication system under Nakagami- $m$ fading. Overlay mode and underlay mode are discussed respectively. To characterize the performance of proposed communication system, we propose novel closed-form analytical expressions for outage probability under two modes, respectively. Based on the analytical results, we derive the diversity order of outage probability. We show that under overlay D2D mode, the diversity order depends on the number of elements and fading parameters. For the underlay D2D case, 0 diversity order is obtained due to the existence of interference. Furthermore, we study the ergodic achievable rate for each mode and the corresponding tight bounds are derived in closed form. High SNR slopes achieved by users under two modes are also discussed. We observe a high SNR slope of order 1 for overlay D2D mode and 0 for underlay D2D mode. In addition, we also investigate the energy efficiency (EE) of the considered system. Numerical results show that the optimal phase shift proposed in our paper enhance system performance effectively comparing to the traditional D2D communication and random phase shift scheme. Significant EE gains can be obtained for low to middle SNR region by passive reflectors with reconfigurable phase. Unlike relay system, the nearer RIS to the D2D transmitter/receiver, the better performance is obtained. [ABSTRACT FROM AUTHOR]

The cloud computing supported heterogeneous cloud radio access network (H-CRAN) is one of the promising solutions to support cellular IoT devices with the legacy cellular systems. However, the dense deployment of small cells with fractional frequency reuse in orthogonal frequency division multiple access (OFDMA) based H-CRANs increases intra- and inter-cell interference, turning the resource allocation into a more challenging problem. In general, the macro cell users are considered as the legacy users, whereas the cellular IoT devices and small cell users share the macro cell users’ resource blocks in an underlaid approach. In this paper, we investigate an underlaid approach of resource allocation for small and macro cell users to improve the energy efficiency (EE) in H-CRANs. The solution approaches are derived with the Dinkelbach, Lagrange multiplier and Alternating Direction Method of Multipliers (ADMM) methods by considering the maximum power, resource block allocation, fronthaul capacity and quality of service (QoS) constraints of macro cell users. A two-step energy efficient underlaid cellular IoT (UC-IoT) supported H-CRAN method is proposed and evaluated with the overlaid cellular IoT (OC-IoT) supported H-CRAN and underlaid H-CRAN without cellular IoT devices. The proposed method is evaluated in terms of energy efficiency and the Jain's fairness index, considering the effect of number of cellular IoT density in each small cell of the H-CRAN. The simulation results demonstrate the effectiveness of the proposed approach compared to earlier approaches. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a reconfigurable intelligent surface (RIS) aided multi-pair communication system, in which multi-pair users exchange information via an RIS. We derive an approximate expression for the achievable rate by assuming that statistical channel state information (CSI) is available. A genetic algorithm (GA) to solve the rate maximization problem is proposed as well. In particular, we consider implementations of RISs with continuous phase shifts (CPSs) and discrete phase shifts (DPSs). Simulation results verify the obtained results and show that the proposed GA method has almost the same performance as the globally optimal solution. In addition, numerical results show that three quantization bits can achieve a large portion of the achievable rate for the CPSs setup. [ABSTRACT FROM AUTHOR]

The wireless-powered communication paradigm brings self-sustainability to the on-vehicle sensors by harvesting the energy from radiated radio frequency (RF) signals. This paper proposes a novel transmission and resource allocation strategy for the scenario where multiple wireless powered vehicle area networks (VAN) co-existed with high density. The considered multi-VAN system consists of a remote master access point (MAP), multiple on-vehicle hybrid access points (HAPs) and sensors. Unlike previous works, we consider that the sensors can recycle the radiated radio frequency energy from all the HAPs when HAPs communicate with MAP, so the dedicated signals for energy harvesting (EH) are unnecessary. The proposed strategy can achieve simultaneous wireless information and power transfer (SWIPT) without complex receiver architecture requirements. The extra EH and interference caused by the dense distribution of VANs, which are rarely explored, are fully considered. To maximize the sum throughput of all the sensors while guaranteeing the transmission from HAPs to the MAP, we jointly optimize the time allocation, system energy consumption, power allocation, and receive beamforming. Due to the non-convexity of the formulated problem, we address the sub-problems separately through the Rayleigh quotient, Frobenius norm minimization and convex optimization. Then an efficient iterative algorithm to obtain sub-optimal solutions. The simulation results and discussions illustrate the proposed scheme's effectiveness and advantages. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a downlink non-orthogonal multiple access (NOMA) transmission scheme for hybrid millimeter-wave (mmWave) system and study its user grouping and power allocation. In order to maximize the weighted sum-rate (WSR) of the system, we first propose a user grouping algorithm based on min-sum message passing (MSMP) strategy under the limited number of radio frequency (RF) chains. Then, with the zero-forcing (ZF) digital precoding, we propose a power allocation scheme for multiple-RF-chain NOMA (MRFC-NOMA) structure based on a non-convex transformation method, and design a low-complexity algorithm. The simulation results show that the proposed joint user grouping and power allocation method with lower complexity can achieve better WSR performance than the traditional schemes. [ABSTRACT FROM AUTHOR]

Vehicle-to-vehicle (V2V) communication has been designed to afford improvements in the traffic congestion and traffic accidents by directly exchanging information between nearby vehicles. However, V2V communication may have difficulty providing service reliability due to interference between V2V links and vehicle-to-cellular user equipment links. In this paper, we consider the transmit power control algorithm to minimize interference among cellular users and vehicles in the context of V2V communication underlaid uplink cellular networks. First, we formulate the problem, which is an NP-hard combinatorial optimization problem with linear constraints. Addressing this problem with traditional optimization methods is ineffective; therefore, we design and train a deep neural network to address this optimization problem. Computational complexity analyses and simulation results reveal that the proposed algorithm outperforms weighted minimum mean squared error (WMMSE), fixed transmit power, and Dinkelbach's methods, and achieves near-global optimum with lower computation complexity than the exhaustive search (ES). [ABSTRACT FROM AUTHOR]

The spectrum usage often comes in an online fashion. Considering the selfish behaviors of both primary users(PUs) and sencond users(SUs), we design online double spectrum allocation methods. We propose a truthful online double auction for spectrum allocation. Preempting existing spectrum usage is not allowed. We design a strategyproof mechanism for both the primary user side and the SU side. In previous studies, users who do not interfere with each other have not been reasonably allocated to use channels. There is one and only one user on the used spectrum channel at a certain time, which will result in discarding many user requests. Our model allows multiple users to use a spectrum channel at the same time. Aiming at the shortcomings of previous research, we propose the concept of grouping for online auctions, so that all SUs that do not interfere with each other can use spectrum channels at the same time. This will greatly increase the number of users who use the spectrum at the same time. We thus increase the utilization rate of the user market, and a large number of users will not be idle and abandoned.In the design of our experiments, the grouping model proposed in this paper has obtained at least $43{\%}$ utilization rate on the set channel, and our experiments have obtained good generality for different interference radius. [ABSTRACT FROM AUTHOR]

In this paper, we investigate security and energy efficiency of multicast communication in cognitive satellite terrestrial networks. To achieve high spectrum efficiency and low interference power transmissions in the cognitive terrestrial network, the rate splitting multiple access scheme (RSMA) is employed to prompt the massive access of the secondary users. In particular, we derive analytical and asymptotic closed-form expressions for secrecy outage probability of the satellite terrestrial network with eavesdropping, interfering, and imperfect channel state information. Hence, a beamforming (BF) scheme based on RSMA for secondary network is proposed to suppress eavesdropping, mitigate interference, and enhance energy efficiency of the proposed system model. Then, we transform non-convex optimization constraints into resoluble problems utilizing Taylor series expansion and successive convex approximation. Finally, simulation results corroborate the above theoretical analysis and highlight the superiority of the designed BF scheme on security and energy efficiency. [ABSTRACT FROM AUTHOR]

Current and future mobile network access technologies increasingly rely on multiantenna transmission techniques and on cell miniaturization to achieve orders-of-magnitude gains in capacity. In this paper, we propose and evaluate the idea of multiuser multiple-input–multiple-input-based (MU-MIMO) cell reassignments. Dense small-cell deployments make it possible to pair user equipment units (UEs), which were originally assigned to different cells, enabling multiuser MIMO (MU-MIMO) and resulting in performance improvements to both UEs. We discuss how such pairings can be accomplished, and we assess the potential gains in the resulting spectral efficiency and MU-MIMO usage. These are assessed through both discussion of performance bounds and detailed system-level simulation in a realistic outdoor small-cell scenario. [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]

In this paper, the downlink of a clustered coordinated multicell multiuser multiple-input multiple-output (MIMO) system is considered, and various low-complexity user scheduling algorithms to maximize the sum rate are proposed. The users' data signals are transmitted cooperatively via the base stations (BSs) of a cluster within the sectorized multicell heterogeneous cellular network. Exhaustive search as the optimal scheduling method is extremely complex, particularly for large numbers of users requesting service. We therefore propose suboptimal scheduling algorithms based on the lower complexity metaheuristic stochastic optimization techniques of simulated annealing (SA) and particle swarm (PS). Moreover, a hybrid algorithm combining the traits of PS and a greedy scheduler is also proposed. The performance and complexity of these algorithms are evaluated for a heterogeneous system model employing different precoding methods. Assessing the algorithms' performance via computer simulations, the effectiveness of the proposed schemes in terms of sum rate is demonstrated, yielding performance very close to that of the exhaustive search at much lower complexity. For each precoding method used in the employed system model, the best corresponding approach to scheduling from our proposed algorithms is determined. [ABSTRACT FROM AUTHOR]

Self-healing networks aim to detect cells with service degradation, identify the fault cause of their problem, and execute compensation and repair actions. The development of this type of automatic system presents several challenges to be confronted. The first challenge is the scarce number of historically reported faults, which greatly complicates the evaluation of novel self-healing techniques. For this reason, in this paper, a system model to simulate faults in Long-Term Evolution (LTE) networks, along with their most significant key performance indicators, is proposed. Second, the expert knowledge required to build a self-healing system is usually not documented. Therefore, in this paper, a methodology to extract this information from a collection of reported cases is proposed. Finally, following the proposed methodology, an automatic fuzzy-logic-based system for fault identification in LTE networks is designed. Evaluation results show that the fuzzy system provides fault identification with a high success rate. [ABSTRACT FROM AUTHOR]

Resource allocation is an important strategy to optimize system performance in multiuser cooperative orthogonal frequency-division multiple-access (OFDMA) systems. In this paper, we jointly consider three different transmission modes in cooperative OFDMA systems, i.e., direct transmission (DT) mode, half-duplex (HD) relay cooperative transmission (HDRCT) mode, and full-duplex (FD) relay transmission (FDRT) mode. The joint optimization problem of transmission mode selection, subcarrier assignment, relay selection, subcarrier pairing, and power allocation (PA) is investigated. In this paper, we transform the binary assignment problem into a maximum-weighted bipartite matching problem, which can be solved by the classical Hungarian method. Based on the dual method, we solve the joint PA and binary assignment problem iteratively. Specifically, since the direct link is considered interference in the FD relay transmission mode, the PA problem in FD relay transmission mode is nontrivial. Thus, we provide a novel hierarchical dual method to solve the PA problem in FD relay transmission mode. In addition, in HDRCT mode, the joint transmission of both the source and relay is taken into account, and we provide a simple and insightful PA scheme. Simulation results show that the proposed algorithms can significantly enhance the overall system throughput, compared with previous works. [ABSTRACT FROM AUTHOR]

In heterogeneous networks (HetNets), energy-efficient resource allocation and intercell-interference management are important issues. In this paper, we address these issues using a two-level dynamic scheme. First, we assign the MUs with the optimum number of subchannels that achieves an operator's required balance between macro users' satisfaction and maximization of network efficiency. Then, the remaining subchannels are left to be shared by a number of small cells. In the latter step, a transmit power adaptation method using a noncooperative game-theoretic approach is developed to reduce cochannel interference in the whole network. The problem is formulated by allowing multiple neighboring small cells to share each subchannel (i.e., universal frequency reuse in the small cell level). We fully characterize the pricing factor in the penalty part of the utility function. The existence and uniqueness of the Nash equilibrium (NE) are analyzed and proved. Then, a distributed iterative algorithm based on the fixed-point theorem is proposed to attain the equilibrium of the game. Simulation results are presented to show the effectiveness of the proposed scheme in different network topologies. [ABSTRACT FROM AUTHOR]

Despite increasing interest in distributed antenna systems (DASs), how to guarantee resource-based fairness in multiuser DASs remains largely unexplored. In this paper, we propose a novel cumulative distribution function (CDF)-based scheduling (CS) with flexible beam transmissions (CSFB) to guarantee resource-based fairness in DASs. With CSFB, to increase the probability that each remote antenna unit (RAU) can contribute to the throughput of users located near it, the probabilities of each user being selected for different RAUs and the number of beams for transmission are jointly adapted to the geographical distribution of RAUs. Thus, CSFB can efficiently exploit multiuser diversity realized by independent fading channels, as well as spatial multiplexing by effectively utilizing the distributed RAUs. To realize CSFB in practice, a one-bit-feedback scheme, i.e., CSFB-OB, is further proposed to reduce feedback overhead for user selection. We prove that both CSFB and CSFB-OB can satisfy resource-based fairness and derive the upper bound for the feedback overhead with CSFB-OB. Simulation results show that CSFB and CSFB-OB with a suitable feedback threshold achieve a better throughput performance than CS with all-beam and single-beam transmissions and the existing fair scheduling schemes. [ABSTRACT FROM AUTHOR]

With the unprecedented new capabilities introduced by modern broadband wireless networks, public safety (PS) agencies are increasingly depending on such networks for their mission-critical communications. One of the key enablers for this adoption is the device-to-device (D2D) communications, where mobile devices can connect directly between each other, without the need for a base station (BS) nor a switching core to handle and route the traffic. This feature is a vital communication backup in case of a network infrastructure failure or a natural disaster. In this paper, we analytically quantify the cellular network performance during massive infrastructure failure, where some terminals can play the role of low-power relay nodes forming multihop communication links to assist farther terminals outside the reach of the healthy network coverage. Namely, we analytically determine the D2D effect in alleviating the damage caused by the disaster. This paper is based on stochastic geometry analysis and presents a novel analytical methodology that is applicable to wide scenarios of network conditions and parameters. This methodology is verified through Monte Carlo simulations for practical network parameters based on the latest Third-Generation Partnership Project (3GPP) recommendations. [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]

This paper studies user-specific clustering for a downlink cloud radio access network (C-RAN), where a central unit (CU), connected to all base stations (BSs) via limited-capacity backhaul links, coordinates the BSs to form cooperative clusters for every user. By taking into account the training overhead for channel estimation in C-RAN, we design the clustering scheme aimed at maximizing the average net throughput of the network subject to the constraint on backhaul capacity, where a hybrid coordinated multipoint (CoMP) transmission mode is considered. The proposed clustering scheme can be operated in a semi-dynamic manner merely based on large-scale channel information, has low computational complexity, and performs close to the optimal scheme found by exhaustive searching. Under two special cases where the backhaul capacity is very stringent and unlimited, the proposed scheme is then tailored for pure coordinated beamforming (CB) mode and pure joint transmission (JT) mode to further reduce the clustering complexity. Simulation results show that the proposed semi-dynamic clustering schemes are superior to the dynamic clustering scheme due to the reduction of required training overhead. [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]

Multipath fading can degrade the performance of a wireless communication system significantly when the data rate is as high as those systems beyond Long-Term Evolution Advanced (LTE-A). To combat the multipath-fading effects, orthogonal frequency-division multiplexing (OFDM) techniques have been extensively studied and used in existing systems. However, another effective method to combat multipath fading is a code-division multiple access (CDMA) scheme, which has not been extensively investigated for relay network communication systems. This paper considers uplink CDMA relay networks (consisting of multiple sources, multiple relays, and a single destination) and downlinks (consisting of a combined source, multiple relays, and multiple destinations) under multipath fading. The objective of this paper is to propose a unique, simple, and effective method of finding optimum nonbinary pseudo noise (PN) spreading and despreading sequences employing a maximum signal-to-interference-plus-noise ratio (SINR) criterion and channel state information (CSI). This paper also examines the sensitivity of the proposed schemes to 1-bit quantization, mistiming alignment, wideband jamming, and imperfect CSI. Simulation results verify that the proposed method shows much faster convergence in finding optimum PN sequences and better performance than existing schemes under the same environment. [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]

This paper presents a coherent scheme to optimize an in-band full-duplex multiple-input–multiple-output (MIMO) relay via beamforming and transmit power allocation in a two-hop single-input–single-output (SISO) link under full channel knowledge and perfect hardware assumptions. First, we derive in closed form the optimal pair of transmit power and receive filter for a fixed transmit filter by unifying the minimum-mean-square-error (MMSE) filtering with the SISO-equivalent power allocation, as an iterative approach is not guaranteed to converge to global optimum. Second, we propose a heuristic algorithm to approximate the optimal transmit filter for a fixed receive filter. Furthermore, we study the well-known null-space projection constraint and derive a singular value decomposition (SVD)-based solution for the arbitrary-rank self-interference channel by generalizing the optimal solution under the assumption of rank-1 self-interference channel. Finally, we combine these solutions into a partially iterative algorithm in order to address the global optimization as our observations justify that some of the aforementioned schemes converge to the optimal solution under certain criteria. The numerical analysis of the proposed iterative algorithm demonstrates close-to-optimal performance relative to the theoretical upper bound of the end-to-end link in terms of maximum achievable throughput. [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]

Providing guaranteed quality of service (QoS) for multimedia applications is a challenging topic in wireless mesh networks (WMNs). This paper proposes a distributed resource reservation (RR) mechanism with novel admission control to guarantee QoS performance of real-time sessions (RTSNs) while improving bandwidth utilization in WMNs. The proposed RR mechanism establishes logical clusters (LCs) for identifying interference relationships between nodes and avoids simultaneous transmissions from interfering nodes. Following the established LCs, a cooperative contention and collision-free channel access is achieved in hybrid medium access control (MAC) for multihop data forwarding in WMNs. To efficiently utilize the scarce resources in a contention-free period, soft and hard resources are reserved for RTSNs according to their QoS demands. This is achieved by a novel admission control algorithm. Furthermore, an analytical model is derived for investigating the RR parameters of the proposed mechanism. Simulation results show that the proposed mechanism guarantees the QoS for RTSNs while improving bandwidth utilization. [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]

Conventional spectrum sharing approaches assume that an unlicensed user accessing a licensed spectrum band autonomously operates by sensing (or detecting) the presence of the primary user, which is licensed to use the given band, with minimal coordination from the primary user. However, in this case, incorrect sensing decisions and resource allocation on the unlicensed secondary users' (SU) part can lead to undesired degradation of the primary users' performance. Therefore, there has been a recent paradigm shift to enable cooperative spectrum sharing, in which interaction is allowed between the primary and the secondary network for efficient spectrum utilization while limiting the interference experienced by a primary user. In this paper, we consider a cooperative spectrum sharing architecture in which the SU is assumed to be a cellular network. We then propose a novel fractional-frequency-reuse-based dynamic resource allocation (DRA) algorithm at the secondary (cellular) network. The joint DRA optimization involves simultaneous spectrum allocation across different base stations and then across users within a base station. It is an NP-hard problem and is prohibitively complex to solve for a large cellular network. Therefore, to reduce the complexity of the joint problem and offer a tractable solution, we formulate layered scheduling algorithms for cross-layer resource allocation. Furthermore, the feedback overhead between the layers is kept minimal. Finally, using simulations, we compare our proposed DRA scheme with other resource allocation schemes for sum system throughput, as well as for fairness in allocation. We also present the result for the case when the available primary spectrum varies over time and locations of SUs. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the problem of channel selection for interference mitigation in opportunistic spectrum access networks using a stochastic game-theoretic approach. The studied network is distributed and dynamic, where each user only has its individual information, and no information exchange is available among users. Moreover, each user is considered to be dynamically active due to its specific data service requirement. Specifically, a user randomly becomes active and then competes for the wireless channel to transmit for a random duration. To capture such dynamic interactions among users, a dynamic interference graph is defined, and based on this, the interference mitigation problem is formulated as a graphical stochastic game. It is proved to be an exact potential game, in which the existence of the Nash equilibrium (NE) is guaranteed. Then, the performance bounds of the NE are theoretically analyzed. Furthermore, we design a fully distributed and online algorithm based on stochastic learning for the interference-mitigation channel selection, which is proved to converge to the NE of the formulated game. Finally, we conduct simulations to validate the effectiveness of the proposed algorithm for interference mitigation and throughput improvement in the distributed and dynamic environment. [ABSTRACT FROM PUBLISHER]

The ultra dense deployment of small cells is considered a key technology to achieve the requested capacity in future cellular networks. However, the interference pattern becomes more unpredictable and challenging in these networks. Therefore, a suitable trade-off between spectrum spatial reuse and interference level has to be pursued to achieve good performance in terms of provided throughput. This paper proposes a new method to maximize the achievable throughput of an UDN with a suitable level of spatial spectrum reuse. In particular, the focus is on the small cells tier where the available spectrum is divided into sub-bands and each cell can use some of these to communicate with its associated users. The goal is to find the sub-bands allocation among cells that maximizes the system throughput. However, to limit complexity and signaling overhead that could result unaffordable in an UDN, a new metric to approximate the cell throughput to be optimized is defined. Moreover, the newly defined problem is solved using the Gibbs Sampling approach. The method effectiveness is proven by comparing the achieved results with those of the maximization of the effective system throughput and the optimal solution. [ABSTRACT FROM AUTHOR]

This paper investigates the capacity gain of full duplex (FD) self-backhauling over the half duplex (HD) counterpart in downlink cellular systems, and then proposes an opportunistic FD scheme. The first step is to derive the capacity gain of FD self-backhauling over the HD counterpart as a function of the system parameters in a computationally tractable form. Unlike previous studies on the capacity of FD self-backhauling, a practical constraint is imposed so that the end-to-end link achieves a target signal-to-interference-plus-noise ratio (SINR) for a successful link connection. Also, a condition under which FD is more beneficial than HD is derived. Specifically, the minimum allowable self interference cancellation factor and the maximum allowable cell radius for the benefit of FD are derived as an explicit function of system parameters. Their dependencies on the system parameters are investigated and compared with counterparts derived for single-hop point-to-point links. Lastly, to overcome the weak points of FD and HD, this paper proposes a user-wise opportunistic FD (OFD) self-backhauled scheme. To this end, an instantaneous channel gain-based FD/HD switching rule is derived from a condition under which FD cannot instantaneously satisfy the target SINR. We confirm the substantial capacity gain of the proposed user-wise instantaneous OFD over a cell-wise static duplex switching scheme, as well as the fixed duplex (HD or FD) schemes. When compared to the static duplex switching scheme, the proposed OFD is most beneficial at the boundary of HD-preferred and FD-preferred regions. Based on this, a system-level guideline is proposed for selecting the most practical scheme among OFD, FD, and HD by trading off capacity gain and switching overhead. Extensive simulation results are provided to confirm the correctness of the derivations and the related investigations. [ABSTRACT FROM AUTHOR]

In heterogeneous multi-cell networks (HetNets), inter-and intra-cell interference are critical issues impairing the performance. In this paper, the frequency-hopping (FH) technique based on an attractive FH sequence (FHS) set with two-level Hamming correlations is exploited in such networks. Motivating from the idea of no-and low-hit-zone FHS sets, a construction algorithm of the new FHS set is proposed by utilizing the interleaving technique. Then, the performance metric of such FHS set in terms of Hamming correlation properties are derived, which are verified by an example. Compared with classic FHS sets (patterns), the proposed FHS set offers a zero Hamming cross-correlation for intra-cell users, and a low Hamming cross-correlation for inter-cell users (i.e., multi-level quality-of-services). The intra-and inter-interference in multi-cell HetNets can be significantly reduced by the proposed sequence-based FH technique. [ABSTRACT FROM AUTHOR]

Code division multiplexing (CDM)-based random access, wherein a set of sequences is reserved for random access and a remote station transmits a random access packet using a sequence randomly selected from this set, is employed in numerous practical wireless systems. If multiple remote stations simultaneously transmit random access packets using the same sequence, the performance degrades owing to sequence collision. In addition, the performance is degraded because of interference if multiple remote stations simultaneously transmit random access packets using different sequences. Therefore, the performance of CDM-based random access is dependent on both sequence collision and interference. There have been no previous studies on analyzing the performance of CDM-based random access considering both sequence collision and interference. In this paper, the throughput of CDM-based random access is investigated considering both sequence collision and interference based on a signal-to-interference-plus-noise ratio (SINR) capture model. Analyses and numerical simulations are performed to compare the throughputs of several random access schemes, including conventional and channel-adaptive random access. The results show that channel-adaptive random access can achieve significantly higher throughput than that achieved by conventional random access. Moreover, the results demonstrate that it is possible to analyze the trade-off between the throughput and implementation complexity with the increased the number of sequences. [ABSTRACT FROM AUTHOR]

In automotive infotainment systems, vehicles using the applications are serviced via continuous infrastructure-to-vehicle (I2V) communications. Additionally, the I2V communications can be combined with vehicle-to-vehicle (V2V) connectivity owing to the small area covered by road side units (RSUs). However, dozens of vehicles have to compete for limited bandwidth when they request service simultaneously in the covered area. In this paper, we propose a joint scheduling and power control scheme for I2V and V2V links in the RSUs’ coverage range. Mapping the I2V and V2V links to tuple-links, we formulate a mixed-integer nonlinear programming (MINLP) problem where frequency scheduler and power controller for those tuple-links are jointly designed. Then, we employ the delayed column generation technique and the transmission pattern definition to decompose the MINLP problem into a transmission pattern scheduling problem, as well as a power control problem. Therein, the transmission pattern scheduling problem is solved by linear programming while a greedy power control algorithm is developed. Simulation results with practical parameter settings show that our proposed scheme outperforms several conventional schemes in terms of service disruption and achieved throughput while maintaining throughput fairness among the requesting vehicles. In particular, a high channel number, a small power level number, and a large buffer size at the requesting vehicles are shown to be helpful for our proposed scheme. [ABSTRACT FROM AUTHOR]

Previous works studied the effect of different system parameters on spectrum-sharing opportunities where secondary users access the spectrum of primary users (PUs). However, a parameter that has received little attention is the spatial size of the field of secondary users. Usually, the field size is assumed to be infinite. Using results developed for infinite fields might be too pessimistic, leading to missing spectrum-sharing opportunities. This paper studies the effect of field size on spectrum-sharing opportunities. We verify that asymptotic results obtained for infinite fields are applicable for finite but relatively large fields (when the radial depth of the field is much greater than the minimum distance to the PU) as well. We also demonstrate that, in some cases, however, asymptotic results are too pessimistic, hiding some spectrum-sharing opportunities. Moreover, this paper shows that, in certain situations, a small reduction in the field size may create spectrum-sharing opportunities, while in certain other situations, a huge increase in the field size may not eliminate spectrum-sharing opportunities. Our study is based on a cumulant-based characterization of the aggregate interference power generated by secondary users. A number of recent papers in literature have dealt with cumulants of the aggregate interference, but only under specific scenarios. We introduce a more comprehensive method to determine the cumulants under various system and channel conditions. These cumulants are utilized to understand the dynamics of the aggregate interference power, approximate its distribution, and, hence, investigate the spectrum-sharing opportunities. [ABSTRACT FROM PUBLISHER]

As an emerging technology in 5G, ultra-dense unmanned aerial vehicles (UAVs) network can significantly improve the system capacity and networks coverage. However, it is still a challenge to reduce interference and improve energy efficiency (EE) of UAVs. In this paper, we investigate a downlink power control problem to maximize the EE in an ultra-dense UAV network. Firstly, the power control problem is formulated as a discrete mean field game (MFG) to imitate the interactions among a large number of UAVs, and then the MFG framework is transformed into a Markov decision process (MDP) to obtain the equilibrium solution of the MFG due to the dense deployment of UAVs. Specifically, a deep reinforcement learning-based MFG (DRL-MFG) algorithm is proposed to suppress the interference and maximize the EE by using deep neural networks (DNN) to explore the optimal power strategy for UAVs. The numerical results show that the UAVs can effectively interact with the environment to obtain the optimal power control strategy. Compared with the benchmarks algorithms, the DRL-MFG algorithm converges faster to the solution of MFG and improves the EE of UAVs. Moreover, the impact of the transmit power on EE under the different heights of the UAVs is also analyzed. [ABSTRACT FROM AUTHOR]

The large spectral bandwidth at millimeter-wave (mmWave) frequencies provides a mean to achieve very high data rates in wireless communication systems. A unique characteristic of mmWave is that mmWave links are very sensitive to blockage and have large propagation path loss, which exhibits low line-of-sight (LoS) probability, unstable connectivity and unreliable communication. This paper studies the influence of the blockage in pedestrian scenario, explains in detail how blockage affects the mmWave propagation characteristics. In particular, we study the behavior of the blockage due to human mobility and how it affects the timescale for outage due to blockage using knife-edge diffraction model (KED). One of the existing solutions to overcome the influence of blockage, is to associate the user equipment (UE) with other available base stations (BSs) by handover (HO) if the serving BS is blocked. In this paper, for a pedestrian scenario, we propose two reinforcement learning (RL) based user association algorithms, which accounts for the past experience of the blockage on the position of the UE. One focuses on the reward to increase the sum LoS probability and is named as blockage-aware user association (BAUA). The other focuses on the reward to balance the trade-off between the throughput and the LoS probability and is named as modified BAUA. We compare the proposed algorithm with the conventional user algorithms such as the maximum throughput based algorithm and the maximum SINR based algorithm. Simulation results show that to increase the sum LoS probability BAUA would be suitable, and to increase the average throughput maximum throughput based method would be suitable. [ABSTRACT FROM AUTHOR]

In this paper, we study radio frequency (RF)-powered underlay cognitive radio networks (CRNs) with power-domain non-orthogonal multiple access (NOMA). In these networks, by using the harvest-then-transmit (HTT) mode, secondary transmitters (STs) can use the harvested energy to simultaneously transmit data based on power-domain NOMA. However, in this mode, the throughput of the secondary system heavily depends not only on the harvested energy, but also on the stringent interference threshold imposed by the primary users. Furthermore, ambient backscatter communication (ABC) has been introduced as a promising technique which enables STs to transmit information by modulating and reflecting ambient RF signals. Therefore, it has the potentiality to be integrated into the RF-powered underlay CR-NOMA networks to improve the throughput of the secondary system. In these networks, each ST works on either the HTT mode or the ABC mode, but not simultaneously. In order to meet the interference constraint of the primary users, STs control their transmit power by finding the appropriate tradeoff between the HTT mode and the ABC mode. We formulate an optimization problem with the goal of achieving the maximum throughput by finding the optimal time resource allocation between the HTT mode and the ABC mode under the strict transmit power constraint at STs. Then the Lagrangian multiplier iterative algorithm is adopted to solve this optimization problem. Simulation results demonstrate that our proposed scheme can significantly improve the performance of the secondary system by comparing it with the other two baseline schemes. [ABSTRACT FROM AUTHOR]

This paper investigates subchannel allocation based on clustered interference alignment in dense small cell networks when all small cell user equipments (SUEs) have differentiated requirements for data streams. By imposing the condition that each cluster has a size not exceeding the maximum value achieved when each SUE needs only one data stream, we maximize the number of SUEs with guaranteed requirements for data streams, which is NP-hard. Hence, we propose a two-phase efficient solution with much lower complexity and reduced feedback overhead. First, similarity clustering is performed by graph partition, and then, subchannel allocation is done through a coloring algorithm. Numerical results show that the proposed solution offers a performance better than the related schemes and close to the approximate optimal solution. [ABSTRACT FROM AUTHOR]

The millimeter wave (mmWave) communication has drawn intensive attention with abundant band resources. In this paper, we consider the popular content distribution (PCD) problem in the mmWave vehicular network. In order to offload the communication burden of base stations (BSs), vehicle-to-vehicle (V2V) communication is introduced into the PCD problem to transmit contents between on-board units (OBUs), and improve the transmission efficiency. We propose a full-duplex (FD) cooperative scheme based on coalition formation game, and the utility function is provided based on the maximization of the number of received contents. The contribution of each member in the coalition can be transferable to its individual profit. While maximizing the number of received contents in the fixed time, the cooperative scheme also ensures the individual profit of each OBU in the coalition. We evaluate the proposed scheme by extensive simulations in mmWave vehicular networks. Compared with other existing schemes, the proposed scheme has superior performances on the number of possessed contents, and system fairness. Besides, the low complexity of the proposed algorithm is demonstrated by the switch operation number, and CPU time. [ABSTRACT FROM AUTHOR]

Ambient backscatter communication (AmBC) over orthogonal-frequency-division-multiplexing (OFDM) signals has recently been proposed as an appealing technique for low power Internet-of-Things (IoT) applications. The special spectrum structure of OFDM signals provides a range of flexibility in terms of bit-error-rate (BER) performance, data rate, and power consumption. In this paper, we study subcarrier-wise backscatter communication over ambient OFDM signals. This new AmBC is to exploit the special spectrum structure of OFDM to transmit data over its squeezed orthogonal subcarriers. We propose a basis transmission scheme, and its two modifications to support a higher data rate with superior BER performance compared to existing methods. The basis scheme can transmit one bit per subcarrier using on-off keying (OOK) modulation in the frequency domain. In the first modification, interleaved subcarrier block transmission model is employed to improve the BER performance of the system in frequency-selective channels. It results in a trade-off between the size of the blocks, and data rate. Thus, in the second modification, interleaved index modulation (IM) is employed to mitigate the data rate decrementation of the former modification. It also stabilizes, and controls the power of the signal to result in interference reduction for a legacy receiver. Analytical, and numerical evaluations provide a proof to see the performance of the proposed method in terms of BER, data rate, and interference. [ABSTRACT FROM AUTHOR]

To be differentiated from the literature, in this paper, we aim to alleviate the impact of pilot contamination (PC) on the massive MIMO systems by cooperatively scheduling users (rather than just assigning) among neighboring cells to share the limited orthogonal pilots. To this end, we develop the multi-cell cooperative scheduling (MCCS) algorithm together with the cooperative scheduling indexes (COSIs) for maximizing the data rate, maximizing the Jain's fairness index and reaching a better tradeoff in-between. For convenience, they are denoted by the COSIs for the CMDR, CMMF and CPF schedulers, respectively. However, its high computational complexity may somehow resists its from practical applications. Thus, a low-complexity cooperative proportional fairness (LC-CPF) algorithm is designed to well approach the MCCS algorithm using the CPF COSI; and at the meantime, the order of computational complexity can be significantly reduced. Moreover, its ability to reach a better tradeoff can still be maintained under the impact of high spectrum-sharing interference. In addition, it is interesting to find that using the proposed cooperative scheduling methods, the open-loop power control mechanism is no longer required for compensating the differences of received signal quality between users. [ABSTRACT FROM AUTHOR]

From the perspective of statistical performance, this correspondence presents an analytical framework to study the interference coordination schemes in two-tier networks with closed-access small-cell base stations (SBSs). We assume the SBSs adopt the combination of power control, access control, and coordinated beamforming to suppress the intertier interference to the macro users (MUEs). Using stochastic geometry, we derive the expressions for the average data rate of users in different tiers. Based on the analytical results, we discuss the optimal transmission schemes of SBSs to maximize the average data rate of small-cell users while guaranteeing the performance of the MUEs. We find that access control is always a suboptimal scheme under the network model in this paper. [ABSTRACT FROM AUTHOR]

In this paper, we propose a full-duplex orthogonal frequency-division multiplexing (OFDM) device-to-device (D2D) system in two-hop networks, where multiple full-duplex decode-and-forward relays assist the transmission from D2D user equipment (DUE) transmitter to DUE receiver. By such a transmission mechanism, the signal transmitted by the DUE transmitter does not need to go through a base station. Meanwhile, due to the adoption of underlay D2D communication protocol, power control mechanisms are thereby necessary to be applied to mitigate the interference to conventional cellular communications. Based on these considerations, we analyze the outage performance of the proposed system, and derive the exact expressions of outage probabilities when bulk and per-subcarrier relay selection criteria are applied. Furthermore, closed-form expressions of outage probabilities are also obtained for special cases when the instantaneous channel state information between BS and cellular user equipments is not accessible, so that a static power control mechanism is applied. Subsequently, we also investigate the outage performance optimization problem by coordinating transmit power among DUE transmitter and relays, and provide a suboptimal solution, which is capable of improving the outage performance. All analyses are substantiated by numerical results provided by Monte Carlo simulations. The analytical and numerical results demonstrated in this paper can provide an insight into the full-duplex relay-assisted OFDM D2D systems, and serve as a guideline for its implementation in next generation networks. [ABSTRACT FROM AUTHOR]

In this correspondence paper, an underlay cognitive radio multicast network, consisting of a cognitive base station (CBS) and multiple multicast groups of secondary users (SUs), is considered. All SUs, belonging to a particular multicast group, are served by the CBS using a common primary user (PU) channel. The goal is to maximize the energy efficiency (EE) of the system, through dynamic adaptation of target rate and transmit power for each multicast group, under the PUs’ individual interference constraint. The optimization problem formulated for this is proved to be nonquasi-concave with respect to the joint variation of the CBS's transmit power and target rate. An efficient iterative algorithm for EE maximization is proposed along with its complexity analysis. Simulation results illustrate the performance gain of our proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, the tradeoff between energy efficiency and spectral efficiency in multicell heterogeneous networks is investigated. Our objective is to maximize both energy efficiency and spectral efficiency of the network, while satisfying the minimum rate requirements of the users. We define our objective function as the weighted summation of energy efficiency and spectral efficiency functions. The fractional frequency reuse (FFR) scheme is employed to suppress intercell interference. We formulate the problem as cell-center boundary selection for FFR, frequency assignment to users, and power allocation. The optimal solution of this problem requires exhaustive search over all cell-center radii, frequency assignments, and power levels. We propose a three-stage algorithm and apply it consecutively until convergence. First, we select the cell-center radius for the FFR method. Second, we assign the frequency resources to users to satisfy their rate requirements and also maximize the objective function. Third, we solve the power allocation subproblem by using the Levenberg–Marquardt method. Minimum rate requirements of users are also included in the solution by using dual decomposition techniques. Our numerical results show a Pareto-optimal solution for energy efficiency and spectral efficiency. We present energy efficiency, spectral efficiency, outage probability, and average transmit power results for different minimum rate constraints. Among other results, we show that, in a particular setting, \text13\% energy efficiency increase can be obtained in a multicell heterogeneous wireless network by sacrificing \text7\% spectral efficiency. [ABSTRACT FROM PUBLISHER]

The main focus of this paper is on multistream multiantenna (multiple-input multiple-output) communications in large-scale heterogeneous random networks. Previous work in this area mainly studies the outage probability from the perspective of a given stream, which is inaccurate as it generally overlooks possible interference-driven cross stream signal-to-interference correlation in each communication link. To tackle this issue, in this paper, we focus on a link-level performance evaluation by characterizing the complementary cumulative distribution function (CCDF) of random mutual information (RMI) under heterogeneous interference. We focus on the scenarios that no coordination among transmitters is persuaded, and the receivers do not attempt to cancel out part of interuser interference. Assume that channel state information is known at both the transmitter and receiver of each communication pair, Rayleigh fading, that the singular value decomposition (SVD) is applied to construct pre-coding/post-coding filters for single-user detection, and that transmitted signals of antennas are i.i.d. Gaussian. We first provide accurate expression for the achievable data rate (ADR) of each link, and show that, regardless of the interference power, when transceivers are equipped with equal number of antennas it grows sublinearly with the number of antennas. We then approximate RMI via Gaussian distribution that its mean is the ADR and its variance is derived based on network's parameters. It is seen that the Gaussian approximation is credible even when two streams of data are transmitted. This paper provides various insights regarding the impact of system parameters, including density of transmitters, path-loss exponent, and the number of antennas, on the ADR and CCDF of RMI. We finally spot tremendous benefits of the SVD scheme over other prominent multiplexing systems, including maximum ratio combining, zero-forcing, and diagonal BLAST superstructure with minimum mean square error receivers. [ABSTRACT FROM PUBLISHER]

Vector perturbation (VP) is a nonlinear precoding technique that achieves near-capacity performance in multiuser multiple-input multiple-output systems at the expense of large complexity due to the search for the optimum perturbation vector. In this paper, we present the hybrid Tomlinson–Harashima VP (TH-VP) algorithm, a novel zero-forcing precoding scheme, which combines TH precoding to remove interuser interference, and VP precoding to equalize each user's multiple spatial streams. We show that the two nonlinear techniques can be integrated in a single optimization and that the proposed algorithm has lower computational requirements than any other. The performance of TH-VP is analyzed and simulation results show that TH-VP outperforms conventional zero-forcing VP and approaches the performance of dirty paper coding. [ABSTRACT FROM AUTHOR]

This paper considers multicell scheduling for coordinated multiple-input multiple-output cellular networks. In a multicell scenario, intercell interference, which is the major challenge degrading system performance, can be suppressed via multicell coordination. However, when the number of users is larger than that can be served, user/multimode selection is necessary, and can significantly enhance the performance in such interference-limited environment. Nevertheless, user selection in a multicell scenario incurs high computational complexity and overhead signalling. To this end, in this paper, low complexity greedy algorithms are proposed for user selection. The algorithms are based on the concept of angle between subspaces and intersection of null spaces, and work in partially distributed fashion with limited information exchange. By these algorithms, channel feedback can be greatly reduced with reasonable computational complexity. In addition, multimode scheduling schemes are proposed for this multicell set up, where the spatial streams are adaptively selected. The proposed algorithms are analysed and compared with the optimal solution obtained by exhaustive search. Simulation results show that the algorithms achieve most of the throughput achievable by the optimal solution. [ABSTRACT FROM AUTHOR]