Showing papers by "Jiandong Li published in 2015"

Energy-Efficient Subcarrier Assignment and Power Allocation in OFDMA Systems With Max-Min Fairness Guarantees

Abstract: In next-generation wireless networks, energy efficiency optimization needs to take individual link fairness into account. In this paper, we investigate a max-min energy efficiency-optimal problem (MEP) to ensure fairness among links in terms of energy efficiency in OFDMA systems. In particular, we maximize the energy efficiency of the worst-case link subject to the rate requirements, transmit power, and subcarrier assignment constraints. Due to the nonsmooth and mixed combinatorial features of the formulation, we focus on low-complexity suboptimal algorithms design. Using a generalized fractional programming theory and the Lagrangian dual decomposition, we first propose an iterative algorithm to solve the problem. We then devise algorithms to separate the subcarrier assignment and power allocation to further reduce the computational cost. Our simulation results verify the convergence performance and the fairness achieved among links, and particularly reveal a new tradeoff between the network energy efficiency and fairness by comparing the MEP with the existing algorithms.

Global energy and water balance: Characteristics from Finite‐volume Atmospheric Model of the IAP/LASG (FAMIL1)

Abstract: This paper documents version 1 of the Finite-volume Atmospheric Model of the IAP/LASG (FAMIL1), which has a flexible horizontal resolution up to a quarter of 1°. The model, currently running on the “Tianhe 1A” supercomputer, is the atmospheric component of the third-generation Flexible Global Ocean-Atmosphere-Land climate System model (FGOALS3) which will participate in the Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition to describing the dynamical core and physical parameterizations of FAMIL1, this paper describes the simulated characteristics of energy and water balances and compares them with observational/reanalysis data. The comparisons indicate that the model simulates well the seasonal and geographical distributions of radiative fluxes at the top of the atmosphere and at the surface, as well as the surface latent and sensible heat fluxes. A major weakness in the energy balance is identified in the regions where extensive and persistent marine stratocumulus is present. Analysis of the global water balance also indicates realistic seasonal and geographical distributions with the global annual mean of evaporation minus precipitation being approximately 10−5 mm d−1. We also examine the connections between the global energy and water balance and discuss the possible link between the two within the context of the findings from the reanalysis data. Finally, the model biases as well as possible solutions are discussed.

Interference Alignment for Partially Connected Downlink MIMO Heterogeneous Networks

Abstract: In this paper, we propose interference alignment (IA) schemes for downlink multiple-input-multiple-output heterogeneous networks (HetNets) with partial connectivity, which is induced by the path loss and the low transmission power of small cells. Specifically, we consider two partially connected scenarios of HetNets. In the first scenario, we focus on the partial connectivity among small cells, whereas in the second scenario, we further consider the partial connectivity between the macrocell and small cells. For the first scenario, we first propose a two-stage IA scheme by exploiting the heterogeneity and partial connectivity of HetNets. Then, the influence of the number of served macro users on system degrees of freedom (DoFs) is investigated. In particular, we derive the condition under which serving one macro user achieves more DoFs than serving multiple macro users and design an algorithm to find the optimal number of served macro users to maximize the system DoFs. Afterward, we study the second scenario and extend the two-stage IA to this scenario. The simulation results show that the proposed IA schemes can significantly improve the system sum rate. Moreover, by considering the partial connectivity between the macro cell and small cells, the system performance can be further improved.

Distributed Subchannel Allocation for Interference Mitigation in OFDMA Femtocells: A Utility-Based Learning Approach

Abstract: Both orthogonal frequency-division multiple access (OFDMA) and femtocell are promising technologies providing subscribers with better services. However, due to the ad hoc nature of femtocells, there is a great challenge to mitigate interference, which may seriously compromise the benefits promised by this novel network architecture. This paper investigates the distributed subchannel allocation (DSA) for cotier interference mitigation in OFDMA-based femtocells, where the femtocells and macrocell transmit on orthogonal subchannels. Particularly, to intuitively study system performance, we formulate this problem as a noncooperative rate maximization game where the utility of each player or femtocell access point is its capacity instead of the incoming interference. Unfortunately, the uncertainty of the existence of the Nash equilibrium for this game makes it difficult to design efficient distributed schemes. To address this issue, we introduce a state space to reflect players' desire for new strategies and then devise a utility-based learning model that requires no information exchange between different players. Utilizing this model, a utility-based DSA algorithm is developed. Moreover, it is analytically shown that the Pareto-optimal solution can be achieved with our proposed algorithm, and as a result, the overall capacity can be efficiently improved, and the system interference can be efficiently mitigated. Finally, simulation results verify the validity of our analysis and demonstrate that our scheme performs comparably or even better compared with the existing strategies, which require information exchange among different femtocells.

Graph-Based User Satisfaction-Aware Fair Resource Allocation in OFDMA Femtocell Networks

Abstract: Unlike the fairness of the number of allocation units studied in the previous works, the fairness of user satisfaction needs to consider the data rates on allocation units. In this paper, we propose a resource-allocation scheme aiming at the max–min fairness of user satisfaction in orthogonal frequency-division multiple access (OFDMA) femtocell networks. The proposed scheme is modeled as an optimization problem with the physical interference model, which is an NP-hard problem. To solve this problem with low computational complexity, we give a solution based on a conflict graph with interference restricted. The proposed conflict graph considers the aggregate of interference and asymmetry of interference, which benefits the solution to approximate that in the physical interference model. Simulation results confirm that the proposed scheme can improve the fairness of user satisfaction effectively.

Throughput–Delay Tradeoff in Interference-Free Wireless Networks With Guaranteed Energy Efficiency

Abstract: Existing works have addressed the tradeoffs between any two of the three performance metrics: throughput, energy efficiency (EE), and delay. In this paper, we unveil the intertwined relations among these three metrics under a unifying framework and particularly investigate the problem of EE-guaranteed throughput–delay tradeoff in interference-free wireless networks. We first propose two admission control schemes, referred to as the first-out and first-in schemes. We then formulate it as two stochastic optimization problems, aiming at throughput maximization (in the first-out scheme) or dropping rate minimization (in the first-in scheme) subject to requirement of EE (RoE), stability, admission control, and transmit power. To solve the problems, the EE-Guaranteed algorithm for throUghput-delAy tRaDeoff (eGuard), respectively called eGuard-I and eGuard-II in the first-out and first-in schemes, is devised. Moreover, with guaranteed RoE, we theoretically show that the eGuard (I and II) can not only push the throughput arbitrarily close to the optimal with tradeoffs in delay but also quantitatively control the throughput–delay performance on demand. Simulation results consolidate the theoretical analysis and particularly show the pros and cons of the two schemes.

End-to-end delay modeling in buffer-limited MANETs: a general theoretical framework

Abstract: This paper focuses on a class of important two-hop relay mobile ad hoc networks (MANETs) with limited-buffer constraint and any mobility model that leads to the uniform distribution of the locations of nodes in steady state, and develops a general theoretical framework for the end-to-end (E2E) delay modeling there. We first combine the theories of Fixed-Point, Quasi-Birth-and-Death process and embedded Markov chain to model the limiting distribution of the occupancy states of a relay buffer, and then apply the absorbing Markov chain theory to characterize the packet delivery process, such that a complete theoretical framework is developed for the E2E delay analysis. With the help of this framework, we derive a general and exact expression for the E2E delay based on the modeling of both packet queuing delay and delivery delay. To demonstrate the application of our framework, case studies are further provided under two network scenarios with different MAC protocols to show how the E2E delay can be analytically determined for a given network scenario. Finally, we present extensive simulation and numerical results to illustrate the efficiency of our delay analysis as well as the impacts of network parameters on delay performance.

Correlation-Based Spectrum Sensing With Oversampling in Cognitive Radio

Abstract: In wireless communication, the amplitude and phase of the transmitted signal have certain patterns during one symbol duration, which introduces high correlation among the samples obtained by oversampling at the receiver. In this work, we aim to explore such correlation information for cognitive radios to enhance the performance of spectrum sensing. By jointly considering the signal modulation, multipath fading, and oversampling rate, we derive the distribution of the empirical autocorrelation function for the obtained samples, on which we propose two efficient spectrum-sensing algorithms, and then analyze their performance. Our theoretical results reveal that the proposed algorithms with oversampling perform strictly better than the conventional energy detection scheme, while requiring the same level of prior information. Finally, we show through simulations that the derived statistical characteristics approximate the true statistical distribution of the autocorrelation function well, and the proposed sensing algorithms significantly improve the sensing performance compared to several existing sensing schemes.

Energy-aware adaptive topology adjustment in wireless body area networks

Abstract: Wireless body area networks (WBANs) represent a key emerging technology to resolve the connection issues on, in or around the human body. One of the most important and challenging issues in WBANs is to maximize the network lifetime. Employing additional relaying node to save energy was considered in the literatures available. Different from the related work, we propose a novel adaptive MAC protocol for WBANs named Network Longevity Enhancement by Energy Aware medium access control Protocol (NLEEAP), which reduces energy consumption without introducing additional devices. The procedures in NLEEAP consist of relay request, relay response and superframe adjustment. The relay operation is initiated when the shortage of a node's residual energy occurs. Once the relay succeeds, NLEEAP smoothly switches the network topology from single-hop to multi-hop. Simulations are conducted and the results show the superiority of NLEEAP in energy efficiency compared with that of existing standard of IEEE 802.15.4.

Past and future direct radiative forcing of nitrate aerosol in East Asia

Abstract: Nitrate as a rapidly increasing aerosol species in recent years affects the present climate and potentially has large implications on the future climate In this study, the long-term direct radiative forcing (DRF) of nitrate aerosol is investigated using State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG) atmospheric general circulation model (AGCM) and the aerosol dataset simulated by a chemical transport model with focus on East Asia The DRF due to other aerosols, especially sulfate, is also evaluated for comparisons Although the chemical transport model underestimates the magnitudes of nitrate and sulfate aerosols when compared with Chinese site observations, some insights into the significances of nitrate climate effects still emerge The present-day global annual mean all-sky DRF of nitrate is calculated to be −0025 W m−2 relative to the preindustrial era, which is much weaker than −037 W m−2 for sulfate However, nitrate DRF may become increasingly important in the future especially over East Asia, given the expectation that decreasing trend in global sulfate continues while the projected nitrate maintains at the present level for a mid-range forcing scenario and even be a factor of two larger by the end of the 21st century for high emission scenarios For example, the anthropogenic nitrate DRF of −20 W m−2 over eastern China could persist until the 2050s, and nitrate is projected to account for over 60 % of total anthropogenic aerosol DRF over East Asia by 2100 In addition, we illustrate that the regional nitrate DRF and its seasonal variation are sensitive to meteorological parameters, in particular the relative humidity and cloud amount It thus remains a need for climate models to include more realistically nitrate aerosol in projecting future climate changes

Propagation Characteristics of Circularly and Linearly Polarized Electromagnetic Waves in Urban Macrocell Scenario

Abstract: Linear polarization (LP) has been the traditional transmission strategy employed in current mobile wireless communication systems. Recently, circular polarization (CP) has regained much interest as CP proves to be a potential candidate to maximize the polarization efficiency component of the link budget. In this paper, the essential concepts of CP are first reinforced by a tutorial description in terms of mathematical insight, propagation characteristics, as well as related applications. Most reported works on CP chiefly focus on the theoretical description of its propagation benefits, such as significant amplitude fade and delay spread (DS) reduction, without simultaneously providing convincing proofs. In other words, CP propagation has not been investigated in sufficient depth. Therefore, we then propose a method for synthesizing CP that is implementation friendly to practical antennas. The engineering validity is subsequently verified by a series of chamber measurements. Intuitively, the polarization trajectory of a synthetical circularly polarized electromagnetic wave is illustrated to further prove the point. Finally, by conducting channel measurement campaigns in a typical urban macrocell scenario, radio propagation characteristics with a dipole as the receive apparatus are analytically extracted for both LP and CP. To facilitate fair competition, the radiation field patterns of two relevant transmitting antennas are intentionally designed to be identical. Numerical results quantitatively demonstrate that, compared with LP, CP can significantly alleviate branch power imbalance between vertical and horizontal polarizations and decrease DS. These advantages are in line with theoretical anticipation and can be fully exploited to upgrade the performance limits of current mobile wireless communication systems.

On-demand scheduling: achieving QoS differentiation for D2D communications

Abstract: As a major supplement to LTE-Advanced, D2D communications underlaying cellular networks have proven efficient in offloading network infrastructures and improving network performance. The scheduling mechanism plays a key role in providing better user experience in D2D communications. However, controlled by operators, D2D communications pose specific problems that do not exist in available wireless networks. Therefore, mature scheduling mechanisms devised for cellular networks or ad hoc networks are not directly applicable to D2D communications. In this article, we first review recent research on scheduling mechanisms for D2D communications, and discuss the design considerations and implementation challenges. Then we propose an on-demand scheduling mechanism, DO-Fast, which can provide QoS differentiation capabilities. Next, we provide performance evaluations based on simulations and an experimental testbed. Finally, we conclude this article and point out possible directions for future research.

Resource allocation in device-to-device communication underlaid cellular network using SCMA: An opportunistic approach

Abstract: Device-to-Device (D2D) communication underlaid cellular network has been proven to enable a significant performance improvement in future fifth generation (5G) wireless networks. Recently, sparse code multiple access (SCMA) has been proposed as an efficient multiple access method to support massive connectivity and diverse applications. In this paper, we incorporate SCMA into D2D communication underlaid cellular network, targeting at enhancing overall network performance. In order to fully exploit the potential of SCMA, we consider that SCMA codebooks can be reused by cellular uplinks and D2D links. However, if not properly handled, the resulting mutual interference may greatly degrade the performance of the hybrid system. To tackle the problem, we have proposed an Opportunistic SCMA Codebook Allocation (OSCA) strategy, aiming to maximize the sum rate of the hybrid system. Specifically, the idea of opportunistic scheduling has been applied in OSCA to implement codebook allocation for cellular user and D2D user. We show via simulation results that the proposed strategy could yield performance enhancement over the conventional strategies in terms of system spectral efficiency.

On Transmission Capacity Region of D2D Integrated Cellular Networks With Interference Management

Abstract: In this paper, we characterize the transmission capacity region (TCR) in D2D integrated cellular networks when two prevalent interference management techniques, power control and Successive Interference Cancellation (SIC) are utilized. The TCR is defined as the enclosure of all feasible sets of active transmitter intensities in cellular and D2D systems. Closed-form approximate expressions of TCR are derived for two spectrum sharing modes, i.e., reuse mode and dedicated mode. The analysis provides insights into the impact of network parameters, interference management methods, as well as bandwidth allocation policy on the TCR. Moreover, we compare the reuse mode and dedicated mode in terms of TCR. Specifically, with power control, given the same target rate for cellular users and D2D users, the TCR of the dedicated mode is shown to be entirely enclosed by that of the reuse mode when $2^{\alpha\over 2}\leq\theta+2$ , where $\alpha$ and $\theta$ are, respectively, the path loss exponent and decoding threshold. However, with SIC utilized, numerical results show that when $\theta>1$ , better performance can always be achieved by the reuse mode in terms of TCR. The results can serve as a guideline for the design of efficient interference management techniques and spectrum regulation in D2D integrated cellular networks.

An iterative reweighted minimization framework for joint channel and power allocation in the OFDMA system

Abstract: We consider the joint channel and power allocation problem for the OFDMA system. The problem is to find a joint channel and power allocation strategy to minimize the total transmission power subject to quality of service constraints and the OFDMA constraint (i.e, at most one user is allowed to access each channel). Since the problem is generally NP-hard, the idea of the existing algorithms is to heuristically allocate the channel and power resources separately. In this paper, we propose a novel iterative reweighted minimization framework based on an effective relaxation, which is beneficial by reformulating the combinatorial OFDMA constraint as an equivalent continuous optimization problem. The proposed framework simultaneously allocates the channel and power resources, and thus is sharply different from the existing ones. Simulation results show the proposed iterative reweighted minimization methods significantly outperform the existing algorithms.

Game Theory Framework Applied to Wireless Communication Networks

Abstract: The popularity of smart phones and other mobile devices has brought about major expansion in the realm of wireless communications. With this growth comes the need to improve upon network capacity and overall user experience, and game-based methods can offer further enhancements in this area. Game Theory Framework Applied to Wireless Communication Networks is a pivotal reference source for the latest scholarly research on the application of game-theoretic approaches to enhance wireless networking. Featuring prevailing coverage on a range of topics relating to the advanced game model, mechanism designs, and effective equilibrium concepts, this publication is an essential reference source for researchers, students, technology developers, and engineers. This publication features extensive, research-based chapters across a broad scope of relevant topics, including potential games, coalition formation game, heterogeneous networks, radio resource allocation, coverage optimization, distributed dynamic resource allocation, dynamic spectrum access, physical layer security, and cooperative video transmission.

A Transformed Conflict Graph-Based Resource-Allocation Scheme Combining Interference Alignment in OFDMA Femtocell Networks

Abstract: To deal with ever-growing wireless services and to increase network throughput, it has been proposed to deploy femtocells with frequency reuse based on orthogonal frequency-division multiple access (OFDMA). However, the interference poses big challenges, particularly for dense deployment scenarios. The resource allocation with joint consideration of subchannel assignment and interference alignment (IA) is different from the traditional problems. First, we need to select the users to perform IA since the number of participant users is limited by the feasibility constraint, and the interference power levels are different due to the path loss. Second, IA increases the degrees of freedom (DoFs) while occupying the additional signal dimension of the participant user; hence, the entirety of the participants in IA require more subchannels compared with the nonparticipants when each of the users transmits the same number of streams. In this paper, we propose a transformed conflict graph-based resource-allocation scheme, where the users are selected according to the effect of IA on the requirement under the feasibility constraint. Then, the subchannel assignment can be modeled as a classical color problem. Extensive simulations show that our scheme can approximate the optimal scheme in a small network and effectively improve the satisfactory ratio of users compared with the scheme without IA in dense femtocell networks.

Adaptive Cross-Network Cross-Layer Design in Heterogeneous Wireless Networks

Abstract: A cross-network cross-layer design method is proposed to exploit the trunking, diversity, and best service assignment gains available in a heterogeneous wireless network (HWN), consisting of orthogonal radio access networks (RANs) and interference-limited RANs. Accounting for traffic-level dynamics and channel fading, we jointly design the distribution strategy for elastic and inelastic traffic, and the radio resource management strategy for RANs, in a network-separable control architecture. Optimal and quantified near-optimal radio allocation schemes are proposed for each type of RAN, which are combined into an on-line design framework that over time provides asymptotically optimal performance, maximizing the sum throughput utility for elastic traffic while guaranteeing the throughput requirements of inelastic traffic. Extensive simulation results demonstrate substantial performance improvement against suboptimal alternatives.

Video delivery in heterogenous crans: architectures and strategies

Abstract: Video traffic has become a major part of mobile data traffic, and will keep growing in the coming years. The performance of video delivery is fundamentally constrained by the structure of the underlying wireless networks. The recently proposed heterogeneous cloud access networks have been widely recognized as an inevitable evolution trend of the current cellular system toward the future 5G system, where multiple hybrid radio access technologies coexist to provide flexible access for mobile users. As a key enabling functional block for high-performance video delivery, a powerful centralized baseband processing unit pool is adopted to control all the radio access technologies, and possibly facilitate the video encoding and transmission, which opens up the potential to achieve higher throughput, lower traffic delay, and greater robustness compared to its basic baseband processing unit counterpart without central control functions. However, such a centralized control framework also raises many new research challenges to be addressed. In this article, we provide an overview of the state-of-the-art video delivery architectures and video packet transmission strategies in heterogeneous cloud radio access networks, with highlights on the networking architectures, transmission strategies, performance analysis, and design challenges. This article also sheds some light on the design principles for future big-dataoriented wireless networks.

Hierarchical Decision-Making With Information Asymmetry for Spectrum Sharing Systems

Abstract: In this paper, observing the information asymmetry phenomenon among multiple secondary users (SUs) spectrum sharing, we analyze the hierarchical decision-making and the strategic interaction of information-poor and information-rich SUs. A Stackelberg capacity-maximization game is formulated with leaders and followers, and closed-form solutions are mathematically derived for the optimal Stackelberg equilibrium solution. Moreover, the existence and uniqueness of equilibrium solutions are investigated via the quasi-variational inequality method. Finally, the distributed algorithm with partial asymmetric information awareness is designed to reach the solution. Numerical results demonstrate that the proposed algorithm achieves improved individual and system performance with mild condition on the ratio of information-poor leaders and information-rich followers.

A Comparative Study on the Dominant Factors Responsible for the Weaker-than-expected El Niño Event in 2014

Abstract: Anomalous warming occurred in the equatorial central-eastern Pacific in early May 2014, attracting much attention to the possible occurrence of an extreme El Nino event that year because of its similarity to the situation in early 1997. However, the subsequent variation in sea surface temperature anomalies (SSTAs) during summer 2014 in the tropical Pacific was evidently different to that in 1997, but somewhat similar to the situation of the 1990 aborted El Nino event. Based on NCEP (National Centers for Environmental Prediction) oceanic and atmospheric reanalysis data, the physical processes responsible for the strength of El Nino events are examined by comparing the dominant factors in 2014 in terms of the preceding instability of the coupled ocean–atmosphere system and westerly wind bursts (WWBs) with those in 1997 and 1990, separately. Although the unstable ocean–atmosphere system formed over the tropical Pacific in the preceding winter of 2014, the strength of the preceding instability was relatively weak. Weak oceanic eastward-propagating downwelling Kelvin waves were forced by the weak WWBs over the equatorial western Pacific in March 2014, as in February 1990. The consequent positive upper-oceanic heat content anomalies in the spring of 2014 induced only weak positive SSTAs in the central-eastern Pacific–unfavorable for the subsequent generation of summertime WWB sequences. Moreover, the equatorial western Pacific was not cooled, indicating the absence of positive Bjerknes feedback in early summer 2014. Therefore, the development of El Nino was suspended in summer 2014.

Time Varying Channel Estimation for DSTC-Based Relay Networks: Tracking, Smoothing and BCRBs

Abstract: In this paper, we examine the channel estimation in an amplify-and-forward (AF) one-way relay network (OWRN) under time selective flat fading scenario, where the distributed space-time coding (DSTC) is adopted at relay nodes. Different from most existing works, our target is to estimate and track the individual channels of each relay hop instead of the composite channels. To reduce the number of the channel parameters to be estimated, we apply the polynomial basis-expansion-model (P-BEM) and convert the problem to estimating the channel coefficient-vectors (called in-BEM-CVs) of each relay hop. With the aid of the autoregressive (AR) model, we formulate the dynamic state space for the in-BEM-CV estimation. Specifically, we adopt the unscented Kalman filter (UKF) to track the in-BEM-CV dynamic variations in an forward manner, and utilize the unscented Rauch-Tung-Striebel smoother (URTSS) to smooth the UKF's estimations in an backward manner. To make the study complete, we also derive Bayesian Cramer lower bounds (BCRBs) for the in-BEM-CV estimation. Finally, numerical results are provided to corroborate the proposed studies.

Robust Joint Transmit Beamforming With QoS Guarantees in Time-Asynchronous DAS

Abstract: This paper studies the joint transmit beamforming optimization in the downlink of a single-cell multiuser distributed antenna system. Due to the distributed nature of transmit antennas, the signals received from different distributed antenna units (DAUs) will experience various transmission delays, and it is difficult to realize accurate symbol-level time synchronization at the user terminal. Thus, we turn to finding a robust joint transmit beamforming algorithm by replacing the received signal-to-interference-plus-noise ratio (SINR) with its lower-bound value. Moreover, the joint transmission incurs huge amount of data sharing among DAUs. Under the per-DAU maximum transmit power constraint, we aim to minimize the system backhaul overhead while satisfying the quality-of-service (QoS) requirement of each user. Since the backhaul overhead minimization requires the transmit beam vectors to have a group sparse structure and is NP-hard, we first make a convex relaxation and then apply the reweighted method to improve the sparsity of the beam vectors. Furthermore, an admission control scheme is applied to guarantee the feasibility of the problem, which iteratively removes the unsatisfied user with the worst quality of experience (QoE) away from the system. Simulation results show that our proposed robust algorithm can achieve a much better performance than the traditional nonrobust algorithm when time asynchronism is less than 30% of the symbol duration and can significantly reduce the system backhaul overhead by designing group sparse transmit beam vectors.

Online and Offline Bayesian Cramér–Rao Bounds for Time-Varying Channel Estimation in One-Way Relay Networks

Abstract: In this paper, we examine the Bayesian Cramer–Rao lower bounds (BCRBs) for the channel estimation in an amplify-and-forward (AF) one-way relay network (OWRN) under the time-selective flat-fading scenario, where the superimposed training is adopted at the relay node in order to achieve the individual channel estimation. We formulate the nonlinear dynamic state space for the individual channels and derive the online/offline BCRBs for the fully data-aided (FDA) channel estimator and the partially data-aided (PDA) estimator. The former estimator has full knowledge about the symbols from both the source and the relay, while the latter one has imperfect statistical information about the data of the source, and possesses full information of the symbols superimposed by the relay. For the FDA scenario, we calculate the closed-form online/offline BCRBs and analyze the effect of the nodes' mobility on the BCRB performance, while for the PDA case, with the assumption of square QAM constellation set at the source, we design one framework to numerically evaluate online/offline BCRBs and analyze the asymptotic BCRBs at high SNRs particularly for the 4-QAM constellation set. Finally, numerical results are provided to corroborate the proposed studies.

Interference-aware spectral-and-energy efficiency tradeoff in heterogeneous networks

Abstract: Heterogeneous networks (HetNets), where multiple low power small cell eNodeBs (SeNBs) are overlaid on the coverage of a high power macrocell eNodeB (MeNB), serve as promising paradigm to enhance spectral efficiency of future cellular wireless networks. To capture the complicated interference interaction and also the coordination behavior among MeNB and SeNBs, this paper proposes a bargaining cooperative game (BCG) framework for interference-aware power coordination in a HetNet. In particular, a new adjustable utility function is employed in the BCG framework to jointly address the spectral and energy efficiencies as well as to achieve the optimal tradeoff between them. We then derive the closed-form power coordination solutions and further propose an interference-aware power coordination scheme with the considerations of both interference mitigation and energy saving. Finally, the numerical results are provided to illustrate the convergence property and efficiency of the proposed power coordination scheme.

Cooperative bargaining game-theoretic methodology for 5G wireless heterogeneous networks

Abstract: Cooperative game-theoretic modelling, analysis and design are critical to mitigate interference and save energy for 5G wireless evolution. Nash axiomatic cooperative game has been widely used to model various cooperation-motivated technical problems, notably in signal processing and communications. However, its most potentials have not been fully exploited, for example, different trade-offs between efficiency and fairness, where efficiency is referred to as both spectral efficiency SE and energy efficiency EE. The trade-offs can be determined by various cooperative solution concepts, for example, the favourable Nash bargaining solution and its rarely studied extensions. Therefore, we first overview the basics of the celebrated Nash bargaining solution and its extensions with geometric interpretations to help better understand them and facilitate distributed algorithm design. Then, both symmetric and asymmetric cooperative game-theoretic frameworks are formulated with different trade-offs incorporating an asymmetric unified β-coefficient determined cooperative game model. As a use case, an α-parameter-related preference function is designed first incorporating both SE and EE. Then, the presented frameworks with the new preference function are studied in a typical heterogeneous network. In the following text, we characterise the effects of β-coefficient to fairness and efficiency and α-parameter to SE and EE. Finally, we conclude the article with the hope of stimulating more interest in cooperative bargaining game and its wider applications in the signalling and communication communities. Copyright © 2014 John Wiley & Sons, Ltd.

Uplink Co-Tier Interference Management in Femtocell Networks With Successive Group Decoding

Abstract: We propose a new scheme to mitigate the uplink co-tier interference in dense femtocell networks, assuming that advanced receivers are employed by the femtocell base stations (FBSs) The conventional solution where interfering cells are assigned orthogonal spectrum resources leads to the inefficient spectrum usage We exploit resource reuse by taking advantage of the successive group decoder (SGD) such that users can opportunistically access the entitled resources of nearby cells The SGD decodes some interference signals in order to best decode the useful signal Multi-cell uplink resource allocation with SGDs is formulated as a joint channel, rate and decoding group (CRG) allocation problem to maximize the weighted sum rates of the variable bit rate (VBR) users while meeting the rate requirements of the guaranteed bit rate (GBR) users Due to the provable NP-hardness of the problem, we propose a greedy algorithm where the idea is to let GBR users opportunistically transmit on the channels of nearby cells and release more interference-free channels for high-rate transmission of VBR users A semi-analytical framework is developed to provide a rough estimate of the potential throughput gain by the proposed technique Simulation results show that the throughput gain over the conventional orthogonal resource allocation ranges from 10%–140% with different traffic proportion, number of users and rate requirement

Achieving Maximum Degrees of Freedom of Two-Hop MIMO Alternate Half-Duplex Relaying System For Linear Transceivers: A Unified Transmission Framework for DF and AF Protocols

Abstract: In this paper, a novel unified transmission framework in the context of both decode-and-forward (DF) and amplify-and-forward (AF) protocols was proposed for a two-hop multiple-input–multiple-output (MIMO) alternate half-duplex (HD) relaying system with $M$ antennas for each node, which can achieve the maximum $M$ degrees of freedom (DoFs) of the system, compared with the existing interference alignment (IA) schemes that can only get $\hbox{3}M/\hbox{4} $ DoF. Furthermore, the proposed schemes require only two relays against three relays invoked in the existing IA schemes. Moreover, the proposed schemes are valid for the cases where the number of antennas $M$ can be either even or odd, whereas the existing IA schemes can only apply for an even number of antennas $M$ .

Graph-based fair resource allocation scheme combining interference alignment in femtocell networks

Abstract: The exponential growth of services demands further increase of spectral efficiency which drives the next generation wireless access networks towards deploying femtocells with frequency reuse. However, the interference will be severe especially in dense deployment scenarios. The fair resource allocation problem by joint consideration of sub-channel assignment and interference alignment (IA) is more complicated than the traditional problem. First, not all the users are appropriate for IA since the number of participant users is limited by the feasibility constraint and the interference power levels are different for the path loss. Second, IA can increase the degrees-of-freedoms while occupy additional signal dimensions of participant users, hence more sub-channels are needed by IA compared with the non-participants when each user transmits the same number of streams. This study models the fair resource allocation problem as an optimisation problem, which is a non-deterministic polynomial-time (NP)-hard. To solve it with low complexity, the authors propose a graph-based scheme to give the approximate solution, where the selection criteria of IA group are based on the influence of IA on the interference graph. Simulation results show that the authors scheme can approximate the optimal solution in a small network and improve the fairness in dense deployment scenarios.