We proposed several energy-efficient resource allocation algorithms for the downlink of an orthogonal frequency-division-multiple-access (OFDMA) based femtocell heterogeneous networks (HetNets). ...Heterogeneous QoS and fairness in rate are investigated in the proposed resource allocation problem. A dense deployment of femtocells in the coverage area of a central macrocell is considered and energy usage of both femtocell and macrocell users are optimized simultaneously. We aim to maximize the weighted sum of the individual energy efficiencies (WSEEMax) and the network energy efficiency (NEEMax) while satisfying the following: (1) minimum throughput for delay-sensitive (DS) users, (2) fairness constraint for delay-tolerant (DT) users, (3) required constraints of OFDMA systems. The problem is formulated in three different forms: mixed 0-1 integer programming formulation, time-sharing formulation and sparsity-inducing formulation. The proposed resource block (RB) and power optimization problems are combinatorial and highly non-convex due to the fractional form of the objective function, the integer constraint of OFDMA RBs and non-affine fairness. We adopt the successive convex approximation (SCA) approach and transform the problems into a sequence of convex subproblems. With the proposed algorithms, we show that the overall joint RB and power allocation schemes converge to suboptimal solutions. Numerical examples confirm the merits of the proposed algorithms.
We consider the downlink of an unmanned aerial vehicle (UAV) assisted cellular network consisting of multiple cooperative UAVs, whose operations are coordinated by a central ground controller using ...wireless fronthaul links, to serve multiple ground user equipments (UEs). A problem of jointly designing UAVs' positions, transmit beamforming, as well as UAV-UE association is formulated in the form of mixed integer nonlinear programming (MINLP) to maximize the sum UEs' achievable rate subject to limited fronthaul capacity constraints. Solving the considered problem is hard owing to its non-convexity and the unavailability of channel state information (CSI) due to the movement of UAVs. To tackle these effects, we propose a novel algorithm comprising of two distinguishing features: (i) exploiting a deep Q-learning approach to tackle the issue of CSI unavailability for determining UAVs' positions, (ii) developing a difference of convex algorithm (DCA) to efficiently solve for the UAV's transmit beamforming and UAV-UE association. The proposed algorithm recursively solves the problem of interest until convergence, where each recursion executes two steps. In the first step, the deep Q-learning (DQL) algorithm allows UAVs to learn the overall network state and account for the joint movement of all UAVs to adapt their locations. In the second step, given the determined UAVs' positions from the DQL algorithm, the DCA iteratively solves a convex approximate subproblem of the original non-convex MINLP problem with the updated parameters, where the problem's variables are transmit beamforming and UAV-UE association. Numerical results show that our design outperforms the existing algorithms in terms of algorithmic convergence and network performance with a gain of up to 70%.
We consider the cell-free massive multiple-input multiple-output (MIMO) downlink, where a very large number of distributed multiple-antenna access points (APs) serve many single-antenna users in the ...same time-frequency resource. A simple (distributed) conjugate beamforming scheme is applied at each AP via the use of local channel state information (CSI). This CSI is acquired through time-division duplex operation and the reception of uplink training signals transmitted by the users. We derive a closed-form expression for the spectral efficiency taking into account the effects of channel estimation errors and power control. This closed-form result enables us to analyze the effects of backhaul power consumption, the number of APs, and the number of antennas per AP on the total energy efficiency, as well as, to design an optimal power allocation algorithm. The optimal power allocation algorithm aims at maximizing the total energy efficiency, subject to a per-user spectral efficiency constraint and a per-AP power constraint. Compared with the equal power control, our proposed power allocation scheme can double the total energy efficiency. Furthermore, we propose AP selections schemes, in which each user chooses a subset of APs, to reduce the power consumption caused by the backhaul links. With our proposed AP selection schemes, the total energy efficiency increases significantly, especially for large numbers of APs. Moreover, under a requirement of good quality-of-service for all users, cell-free massive MIMO outperforms the colocated counterpart in terms of energy efficiency.
This paper studies beamforming techniques for energy efficiency maximization (EEmax) in multiuser multiple-input single-output (MISO) downlink system. For this challenging nonconvex problem, we first ...derive an optimal solution using branch-and-reduce-and-bound (BRB) approach. We also propose two low-complexity approximate designs. The first one uses the well-known zero-forcing beamforming (ZFBF) to eliminate inter-user interference so that the EEmax problem reduces to a concave-convex fractional program. Particularly, the problem is then efficiently solved by closed-form expressions in combination with the Dinkelbach's approach. In the second design, we aim at finding a stationary point using the sequential convex approximation (SCA) method. By proper transformations, we arrive at a fast converging iterative algorithm where a convex program is solved in each iteration. We further show that the problem in each iteration can also be approximated as a second-order cone program (SOCP), allowing for exploiting computationally efficient state-of-the-art SOCP solvers. Numerical experiments demonstrate that the second design converges quickly and achieves a near-optimal performance. To further increase the energy efficiency, we also consider the joint beamforming and antenna selection (JBAS) problem for which two designs are proposed. In the first approach, we capitalize on the perspective reformulation in combination with continuous relaxation to solve the JBAS problem. In the second one, sparsity-inducing regularization is introduced to approximate the JBAS problem, which is then solved by the SCA method. Numerical results show that joint beamforming and antenna selection offers significant energy efficiency improvement for large numbers of transmit antennas.
We investigate the spectral efficiency of full-duplex small cell wireless systems, in which a full-duplex capable base station (BS) is designed to send/receive data to/from multiple half-duplex users ...on the same system resources. The major hurdle for designing such systems is due to the self-interference at the BS and co-channel interference among users. Hence, we consider a joint beamformer design to maximize the spectral efficiency subject to certain power constraints. The design problem is first formulated as a rank-constrained optimization problem, and the rank relaxation method is then applied. However, the relaxed problem is still nonconvex, and thus, optimal solutions are hard to find. Herein, we propose two provably convergent algorithms to obtain suboptimal solutions. Based on the concept of the Frank-Wolfe algorithm, we approximate the design problem by a determinant maximization program in each iteration of the first algorithm. The second method is built upon the sequential parametric convex approximation method, which allows us to transform the relaxed problem into a semidefinite program in each iteration. Extensive numerical experiments under small cell setups illustrate that the full-duplex system with the proposed algorithms can achieve a large gain over the half-duplex system.
Reconfigurable intelligent surfaces (RISs) represent a new technology that can shape the radio wave propagation in wireless networks and offers a great variety of possible performance and ...implementation gains. Motivated by this, we study the achievable rate optimization for multi-stream multiple-input multiple-output (MIMO) systems equipped with an RIS, and formulate a joint optimization problem of the covariance matrix of the transmitted signal and the RIS elements. To solve this problem, we propose an iterative optimization algorithm that is based on the projected gradient method (PGM). We derive the step size that guarantees the convergence of the proposed algorithm and we define a backtracking line search to improve its convergence rate. Furthermore, we introduce the total free space path loss (FSPL) ratio of the indirect and direct links as a first-order measure of the applicability of RISs in the considered communication system. Simulation results show that the proposed PGM achieves the same achievable rate as a state-of-the-art benchmark scheme, but with a significantly lower computational complexity. In addition, we demonstrate that the RIS application is particularly suitable to increase the achievable rate in indoor environments, as even a small number of RIS elements can provide a substantial achievable rate gain.
The paper reviews recent models that have applied the techniques of behavioural economics to the analysis of the tax compliance choice of an individual taxpayer. The construction of these models is ...motivated by the failure of the Yitzhaki version of the Allingham–Sandmo model to predict correctly the proportion of taxpayers who will evade and the effect of an increase in the tax rate upon the chosen level of evasion. Recent approaches have applied non‐expected utility theory to the compliance decision and have addressed social interaction. The models we describe are able to match the observed extent of evasion and correctly predict the tax effect but do not have the parsimony or precision of the Yitzhaki model.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Understanding the evidence-based elements that impact the adoption of organic farming is advantageous for the proper management of such adoption. Our research examines the influence of ...socio-psychological factors in promoting organic agriculture in Vietnam, including peer influence, social norms and personal norms. Cluster analysis is applied to account for individuals' heterogeneity in environmental beliefs regarding adopting organic farming. We find that peer influence, such as the frequency of communication and the existence of organic farming neighbors, are critical components of organic agriculture. Moreover, social and personal norms could also play a key role in incentivizing environmentally concerned farmers to convert to organic farming. Therefore, policymakers should encourage neighborhood collaboration, establish a channel for farmers to promote interaction between farmers and promote farmers’ recognition of the importance of organic agriculture to effectively drive them toward the sustainable adoption of organic farming.
•Neighborhood organic farmers are important factors promoting organic farming conversion.•Frequency of communications with other organic farmers is essential to promote farmer-to-farmer links.•Descriptive norm could generate social pressure and shape individuals toward more organic agriculture.•Information about organic farming benefits could shift farmers' perceptions and drive them toward sustainable agriculture.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
To mitigate the computational power gap between the network core and edges, mobile edge computing (MEC) is poised to play a fundamental role in future generations of wireless networks. In this ...correspondence, we consider a non-orthogonal multiple access (NOMA) transmission model to maximize the worst task to be offloaded among all users to the network edge server. A provably convergent and efficient algorithm is developed to solve the considered non-convex optimization problem for maximizing the minimum number of offloaded bits in a multi-user NOMA-MEC system. Compared to the approach of optimized orthogonal multiple access (OMA), for given MEC delay, power and energy limits, the NOMA-based system considerably outperforms its OMA-based counterpart in MEC settings. Numerical results demonstrate that the proposed algorithm for NOMA-based MEC is particularly useful for delay sensitive applications.
Haber-Bosch (HB) process, the main method for ammonia (NH3) production, contributes to near 2% of the global carbon emissions because the hydrogen input is obtained from fossil sources. NH3 ...production is concentrated in a few countries, adding emissions due to global distribution. Distributed plants next to farmers and fed by renewable energy can reduce these impacts, as well as NH3 storage, shortage risks, and price volatility. Distributed plants cannot reach low NH3 production costs as centralised plants, but they can be promoted by the environmental benefits of its products lifecycles. Therefore, life cycle assessments of NH3 production pathways and specific modelling for NH3 transport in Australia were performed, from cradle-to-site, to identify the influence of storage, transport, and energy sources in their environmental profiles. The carbon footprint of centralised production was up to 2.96 kg.CO2-eq/kg.NH3, from which 29.3% corresponded to transport. Local production demonstrated substantial avoided transport impacts and that CO2-eq can reach reductions over 100% when including co-product credits such as oxygen and carbon black. Local plants using electrolysers to supply mini-HB loops obtained rates of 0.12, −0.52, and −1.57 kg.CO2-eq/kg.NH3 using electricity from solar, wind, and biogas (other than manure) sources, respectively. The alternative using high temperature plasma reactor instead of electrolyser obtained its best rate of −0.65 kg.CO2-eq/kg using biogas different from manure. At farm electrolyser-based plants using novel non-thermal plasma reactors, considering potential energy yields and simplified NH3 separation technology, could reach a rate of −1.07 kg.CO2-eq/kg.NH3, using solar energy. Among the assessed pathways, the most notable impact was on freshwater eutrophication in the electrolyser-based plants generating reductions up to 290%, due to oxygen credits. Despite these results, the use of solar energy raises concerns on land use and terrestrial ecotoxicity due to the area needed for solar farms and the manufacture of their components.
Display omitted
•Life cycle assessments for NH3 production, storage, and distribution were performed.•Transport can add up to 867 t of CO2-eq per each million-tonne of NH3.•Small-scale NH3 plants are environmentally friendly if renewable energy is used.•Non-thermal plasma reactors can solve flexibility drawbacks of Haber-Bosch process.•Oxygen and carbon black credits can invert the carbon balance of NH3 production.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
PDF
