Low-complexity Power Allocation Research Articles

Performance Analysis of Power Allocation and User-Pairing Techniques for MIMO-NOMA in VLC Systems

In this paper, we evaluate the performance of multiple-input multiple-output (MIMO) communication systems applied with a non-orthogonal multiple access (NOMA)-based indoor visible light communication (VLC). We present two efficient user-pairing algorithms for NOMA in VLC, aiming to enhance achievable data rates effectively. Our investigation involves the application of three low-complexity power allocation techniques. Comparative analysis reveals performance enhancements when employing the proposed schemes, especially when contrasted with NOMA without user pairing and orthogonal frequency division multiple access (OFDMA). Additionally, we explore the performance of both algorithms in scenarios with both even and odd numbers of users. Simulation results demonstrate the superiority of NOMA in comparison to OFDMA.

Low complexity joint spectrum resource and power allocation for ultra dense networks

In this paper, we propose a low complexity spectrum resource allocation scheme cross the access points (APs) for the ultra dense networks (UDNs), in which all the APs are divided into several AP groups (APGs) and the total bandwidth is divided into several narrow band spectrum resources and each spectrum resource is allocated to APGs independently to decrease the interference among the cells. Furthermore, we investigate the joint spectrum and power allocation problem in UDNs to maximize the overall throughput. The problem is formulated as a mixed-integer nonconvex optimization (MINCP) problem which is difficult to solve in general. The joint optimization problem is decomposed into two subproblems in terms of the spectrum allocation and power allocation respectively. For the spectrum allocation, we model it as a auction problem and a combinatorial auction approach is proposed to tackle it. In addition, the DC programming method is adopted to optimize the power allocation subproblem. To decrease the signaling and computational overhead, we propose a distributed algorithm based on the Lagrangian dual method. Simulation results illustrate that the proposed algorithm can effectively improve the system throughput.

Beam Domain MIMO-OFDM Optical Wireless Communications With PAPR Reduction

Multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM), confirmed as an efficient technique, has been applied in optical wireless communications (OWCs) to improve the transmission rate. However, the disadvantage of high peak-to-average power ratio (PAPR) also brings into the OWC systems, especially for multi-user communications, resulting in low power efficiency. This paper proposes beam domain MIMO-OFDM OWCs with PAPR reduction. We describe the MIMO-OFDM OWC system architecture and derive the achievable sum rate and PAPR for multi-user OFDM systems, which are dominated by the precoding vectors. To reduce the PAPR, we design the precoding vectors to maximize the sum rate under the PAPR constraint. We propose an iterative process to obtain a candidate optimal solution by the sequential parametric convex approximation (SPCA) method. Furthermore, we prove that the PAPR increases with the number of users and propose a low complexity beam scheduling and power allocation algorithm. Numerical results validate that the proposed schemes can efficiently improve the transmission rate and reduce the PAPR.

Low-Latency Oriented Resource Allocation for MEC-Assisted Adaptive Bitrate Video Streaming

This paper focuses on low-latency transmissions for mobile edge computing (MEC)-assisted adaptive bitrate (ABR) video streaming. With the aim to realize minimum video service latency, an optimization problem is formulated by jointly designing caching, computing and power allocation, subject to diverse video version downloading rate requirements and the limited resources of MEC servers. The formulated optimization problem turns out to be a mixed integer nonlinear programming (MINLP) problem. To solve the problem and satisfy the low-latency service requirement of ABR video streaming, a low-complexity two-step iterative algorithm is proposed by decomposing the MINLP problem into two subproblems, a joint caching and computing subproblem and a power allocation subproblem. Due to the highly coupled nature of the caching and computing, the first subproblem is an integer nonlinear programming (INLP) problem. To solve it efficiently, the INLP problem is equivalently transformed into an integer linear programming (ILP) problem, which is thereafter solved by MATLAB intlinprog function. The second subproblem is a convex problem and is solved by low-complexity power allocation (LCPA) algorithm. Intensive simulation results show that the proposed algorithm converges in a very short time, and can significantly reduce the average latency compared to the state-of-the-art baselines.

A novel user clustering and a low-complexity power allocation in multi-user and multi-cluster NOMA system via Stackelberg game competition

Non-orthogonal multiple access (NOMA) has drawn wide attentions in multi-user, resource-constrained mobile systems to improve the system spectral efficiency. In the conventional resource assignment approaches, the optimal power allocation solutions are usually performed among multiple clusters, which, however, incur a high computational complexity due to the diversity of multiple users. In this work, we aim at the practical scenarios of multi-user and multi-cluster NOMA networks with the proposed a low-complexity power allocation and a suboptimal user clustering approach. By using Stackelberg game competition, a closed-form solution with no iterative operations is given first to the power allocation problem. The main idea of the authors’ proposed scheme is to have the base station (BS) allocating resources to all the users freely to guarantee their required minimum transmission-rates, and obtaining the maximal revenue through selling the remaining resources. Then, a suboptimal user clustering approach is further proposed to obtain more revenue for selling the resource. Numerical results show that the proposed power allocation scheme approximates the optimal sum-rates performance, but with lower computational floating-point operations (FLOPs) for the multi-user scene. And, the given user clustering scheme can pursue more revenue of the BS.

CoMP-Assisted NOMA and Cooperative NOMA in Indoor VLC Cellular Systems

In this paper, we investigate the dynamic power allocation for a visible light communication (VLC) cellular system consisting of two coordinating attocells, each equipped with one access-point (AP). The coordinated multipoint (CoMP) between the two cells is introduced to assist users experiencing high inter-cell-interference (ICI). Specifically, the coordinated zero-forcing (ZF) precoding is used to cancel the ICI at the users located near the centers of the cells, whereas the joint transmission (JT) is employed to eliminate the ICI at the users located at the edge of both cells and to improve their receptions as well. Furthermore, two multiple access techniques are invoked within each cell, namely, non-orthogonal-multiple-access (NOMA) and cooperative non-orthogonal-multiple-access (C-NOMA). Hence, two multiple access techniques are proposed for the considered multi-user multi-cell system, namely, the CoMP-assisted NOMA scheme and the CoMP-assisted C-NOMA scheme. For each scheme, two power allocation frameworks are formulated each as an optimization problem, where the objective of the former is maximizing the network sum data rate while guaranteeing a certain quality-of-service (QoS) for each user, whereas the goal of the latter is to maximize the minimum data rate among all coexisting users. The formulated optimization problems are not convex, and hence, difficult to be solved directly unless using heuristic methods, which comes at the expense of high computational complexity. To overcome this issue, optimal and low complexity power allocation schemes are derived. In the simulation results, the performance of the proposed CoMP-assisted NOMA and CoMP-assisted C-NOMA schemes are compared with those of the CoMP-assisted orthogonal-multiple-access (OMA) scheme, the C-NOMA scheme and the NOMA scheme, where the superiority of the proposed schemes are demonstrated. Finally, the performance of the proposed schemes and the considered baselines is evaluated while varying various system parameters.

Spatial-Spectral Terahertz Networks

This paper focuses on the spatial-spectral terahertz (THz) networks, where transmitters equipped with leaky-wave antennas send information to their receivers at the THz frequency bands. As a directional and nearly planar antenna, the leaky-wave antenna allows for information transmissions with narrow beams and high antenna gains. The conventional large antenna arrays are confronted with challenging issues such as scaling limits and path discovery in the THz frequencies. Therefore, this work exploits the potential of leaky-wave antennas in the dense THz networks, to establish low-complexity THz links. By addressing the propagation angle-frequency coupling effects, the transmission rate is analyzed. The results show that the leaky-wave antenna is efficient for achieving the high-speed transmission rate. The co-channel interference management is unnecessary when the THz transmitters with large subchannel bandwidths are not extremely dense. A simple subchannel allocation solution is proposed, which enhances the transmission rate compared with the same number of subchannels with the equal allocation of the frequency band. After subchannel allocation, a low-complexity power allocation method is proposed to improve the energy efficiency.

An Optimum Weighted Energy Efficiency Approach for Low Complexity Power Allocation in Downlink NOMA

Non-orthogonal multiple access (NOMA) has emerged as a significant technique for 5G wireless networks because it increases device connectivity, spectral efficiency, and energy efficiency. The advantages of the NOMA system rely on the employed resource allocation schemes, which include power allocation (PA) and subcarrier user assignment (SUA). Therefore, this paper concentrates on suggesting a PA approach called a weighted energy efficiency power allocation (WEE-PA) approach to maximize the total weighted energy efficiency (WEE) in the NOMA system. Also, the proposed WEE-PA approach boosts the fairness between users, the minimum user rate in the system, the outage probability, and the average data rate per weak user. Therefore, the PA optimization problem defines as an optimization problem with a total power constraint and a set of dynamic PA parameters to maximize the WEE and ensure user fairness. The original optimization problem separates into two sub-problems, and an iterative approach is employed to solve these two sub-problems alternatingly and reduce the computational complexity. Since the optimization problem is non-convex, the sequential quadratic programming (SQP) technique is applied to resolve it and find the corresponding optimal solution. Our simulations confirm that using our proposed WEE-PA algorithm to allocate mutual resources furnishes better results than existing PA schemes.

Low-Complexity Power Allocation in Pilot-Pouring Superimposed-Training Over CB-FMT

Pilot-pouring superimposed training (PPST) is a novel channel estimation technique specially designed for cyclic block filtered multi-tone (CB-FMT), where the pilot symbols are poured into the subcarriers taking advantage of the power left unused by the data symbols. Hence, since this technique is based on superimposed training (ST) principles, the data rate is not reduced, unlike the pilot symbol assisted modulation (PSAM). Besides, it exploits a weighted average at the receiver side that is capable of minimizing the mean squared error (MSE) of the channel estimation, and then enhancing the performance of the system. However, the existing proposal on PPST is limited to the minimization of the MSE to improve channel estimation for a given power allocation factor, without solving the joint optimization of channel estimation and data detection procedures. With this aim, this work addresses the whole problem to reach the best performance for both tasks, thus taking into account also the power allocation factor in the optimization process, where the spectral efficiency must be maximized through the signal-to-interference plus noise ratio (SINR). Two optimization approaches are proposed, where the first one, referred as pilot-pouring optimization (PPO), is focused on performance at the expense of a high complexity, while the second one, denoted as low-complexity PPO (LPPO), is able to trade-off between performance and execution time. Numerical results are provided in order to show the validity of our proposal, where the different optimization problems are compared in terms of SINR and execution time.

A novel low-complexity power allocation algorithm based on the NOMA system in a low-speed environment

For future wireless communication systems, Power Domain Non-Orthogonal Multiple Access (PD-NOMA) using an advanced receiver has been considered as a promising radio access technology candidate. Power allocation plays an important role in the PD-NOMA system because it considerably affects the total throughput and Geometric Mean User Throughput (GMUT) performance. However, most existing studies have not completely accounted for the computational complexity of the power allocation process when the User Terminals (UTs) move in a slow fading channel environment. To resolve such problems, a power allocation method is proposed to considerably reduce the search space of a Full Search Power (FSP) allocation algorithm. The initial power reallocation coefficients will be set to start with former optimal values by the proposed Lemma before searching for optimal power reallocation coefficients based on total throughput performance. Step size and correction granularity will be adjusted within a much narrower power search range while invalid power combinations may be reasonably discarded during the search process. The simulation results show that the proposed power reallocation scheme can greatly reduce computational complexity while the total throughput and GMUT performance loss are not greater than 1.5% compared with the FSP algorithm.

A Low Computational Complexity Power Allocation Algorithm Based on Greedy Policy

A Low Computational Complexity Power Allocation Algorithm Based on Greedy Policy

ENERGY-EFFICIENT POWER ALLOCATION FOR IMPERFECT CSI DOWNLINK NOMA SYSTEM

The fifth generation (5G) networks must provide the massively increased number of users by thousand times higher data rate at lower power consumption. Thus, optimizing the energy efficiency (EE) becomes an essential issue that has to be researched from the green communication perspective. Non-orthogonal multiple access (NOMA) is considered one of the high potential techniques in fifth-generation systems. This technology is favorable to maximize the energy efficiency and the spectrum efficiency by composing different signals at the same time on the same carrier at different power levels. In this paper, a low complexity power allocation algorithm is proposed in imperfect channel state information (CSI) downlink NOMA cellular system, where obtaining full CSI at the base station is considered a challenge. The proposed algorithm relies on the fact that the allocated power is inversely proportional to the channel strength of the user to implement the successive interference cancellation (SIC) technique at the user terminal to reconstruct the desired signal. The performance of the system is analyzed in terms of energy efficiency and outage probability and compared to the conventional orthogonal multiple access (OMA) system. Results show that the proposed algorithm increases the energy efficiency by about 50% compared to the conventional OMA technology, and an improvement in the outage probability has been achieved. Furthermore, the effect of the error in the channel estimation on the energy efficiency in imperfect CSI NOMA system is evaluated. The simulation shows that the energy efficiency reduces when the channel estimation error increases; and the best performance is achieved in the perfect CSI case where the channel estimation error is zero.

NOMA for Energy-Efficient LiFi-Enabled Bidirectional IoT Communication

In this paper, we consider a light fidelity (LiFi)-enabled bidirectional Internet of Things (IoT) communication system, where visible light and infrared light are used in the downlink and uplink, respectively. In order to improve the energy efficiency (EE) of the bidirectional LiFi-IoT system, non-orthogonal multiple access (NOMA) with a quality-of-service (QoS)-guaranteed optimal power allocation (OPA) strategy is applied to maximize the EE of the system. We derive a closed-form OPA set based on the identification of the optimal decoding orders in both downlink and uplink channels, which can enable low-complexity power allocation. Moreover, we propose an adaptive channel and QoS-based user pairing approach by jointly considering users' channel gains and QoS requirements. We further analyze the EE of the bidirectional LiFi-IoT system and the user outage probabilities (UOPs) of both downlink and uplink channels of the system. Extensive analytical and simulation results demonstrate the superiority of NOMA with OPA in comparison to orthogonal multiple access (OMA) and NOMA with typical channel-based power allocation strategies. It is also shown that the proposed adaptive channel and QoS-based user pairing approach greatly outperforms individual channel/QoS-based approaches, especially when users have diverse QoS requirements.

Energy-Efficient Decoupled Access Scheme for Cellular-Enabled UAV Communication Systems

This article proposes a decoupled access scheme with enhanced energy efficiency (EE) for cellular networks serving a mix of randomly distributed ground and areal users. While unmanned aerial vehicles (UAVs) benefit from line-of-sight (LOS) dominant channels with their serving base-stations (BSs), their omnidirectional antennas could cause high interference to ground users (GUEs). To overcome this, a downlink (DL) and uplink (UL) decoupled (DUDe) access scheme is proposed in which the UAVs’ control and nonpayload communication links are separated from the high-capacity data links by connecting to different BSs and transmitting over different frequency bands in the UL and DL directions. The GUE-BS channels are also decoupled in tandem to minimize interference. Moreover, as battery life is a major constraint for UL transmissions, an optimal low-complexity power allocation algorithm—based on fractional programming and successive convex approximation—is proposed for optimizing the EE of this DUDe scheme. Our numerical results demonstrate that the proposed scheme can achieve several times higher sum-rates in both UL and DL directions than its coupled benchmark counterparts. Moreover, it will be shown that in addition to improving the GUE sum-rate by 15%, the devised power allocation algorithm achieves twice higher GUE EE than conventional fractional power control.

Capacity Loss From Localization Error in MIMO Channel Using Leaky Coaxial Cable

Leaky coaxial (LCX) cable has been employed as antennas for wireless traffic over many linear-cell scenarios such as railway station, tunnels and shopping malls. In addition, LCX can be used for user localization and wireless power transfer (WPT). Compared with the equal power allocation method, the power allocation method for LCX system using positional information (PI) can improve its capacity with the same level of computational complexity. In this paper, we will investigate the level of capacity loss on the 2.4 GHz and 5 GHz band for the conventional equal power (EP) allocation method, the water-filling (WF) based power allocation, and our proposed low-complexity power allocation method for LCX system with PI. The results show that LCX system with our proposed method using PI can reduce the capacity loss due to localization error than that of others.

Low-Complexity Power Allocation for Network-Coded User Scheduling in Fog-RANs

Consider a Fog Radio Access Network (FRAN) in which a cloud base station (CBS) is responsible for scheduling user-equipments (UEs) to a set of radio resource blocks (RRBs) of Fog Access Points (F-APs) and for allocating power to the RRBs. The conventional graphical approach for solving the coordinated scheduling and power control problem in FRAN requires prohibitive computational complexity. This letter, instead, proposes a low-complexity solution to the problem under the constraint that all the scheduled UEs can decode the requested files sent by their associated RRBs/F-APs. Unlike previous solution that requires constructing the total power control graph, the proposed computationally efficient solution is developed using a single power control subgraph. Numerical results reveal a close-to-optimal performance of the proposed method in terms of throughput maximization for correlated channels with a significant reduction in the computational complexity.

Efficient Downlink Power Allocation Algorithms for Cell-Free Massive MIMO Systems

Cell-free Massive MIMO systems consist of a large number of geographically distributed access points (APs) that serve the users by coherent joint transmission. The spectral efficiency (SE) achieved by each user depends on the power allocation: which APs that transmit to which users and with what power. In this article, we revisit the max-min and sum-SE power allocation policies, which have previously been approached using high-complexity general-purpose solvers. We develop and compare several different high-performance low-complexity power allocation algorithms that are appropriate for use in large systems. We propose two new algorithms for sum-SE power optimization inspired by weighted minimum mean square error (WMMSE) minimization and fractional programming (FP). Further, one new FP-based algorithm is proposed for max-min fair power allocation. The alternating direction method of multipliers (ADMM) is used to solve specific convex subproblems in the proposed algorithms. Our ADMM reformulations lead to multiple small-sized subproblems with closed-form solutions. The proposed algorithms find global or local optimal power allocation solutions for large-scale systems but with reduced computational time compared to previous work.

Joint relay selection and power allocation for NOMA‐based multicast cognitive radio networks

In this study, the problem of joint relay selection and power allocation (J-RS-PA) for NOMA-based multicast cognitive radio networks is considered. In particular, the aim is to simultaneously maximise the end-to-end SINR/SNR of the primary and secondary transmitter–receiver (TR) pairs, subject to quality-of-service (QoS) constraints. Communication between the primary and secondary TR pairs is performed over two-phases, namely, the broadcasting phase, and the cooperation phase. In the broadcasting phase, the primary and secondary transmitters broadcast their data symbols; while in the cooperation phase, the selected relay forwards the decoded symbols to their intended receivers. However, the formulated J-RS-PA problem happens to be non-convex, resulting in computationally-prohibitive complexity. Consequently, an optimal low-complexity two-stage relay selection and power allocation (TS-RS-PA) algorithm is devised, which is based on the solution of linear programming problem reformulations. Simulation results are presented to validate the proposed TS-RS-PA algorithm, which is shown to yield the optimal SINR/SNR values in comparison to the J-RS-PA scheme, but with lower computational complexity, while satisfying QoS constraints.

An Efficient Resource Allocation for Massive MTC in NOMA-OFDMA Based Cellular Networks

To alleviate random access congestion and support massive-connections with less energy consumption for machine-type communications (MTC) in the 5G cellular network, we propose an efficient resource allocation for massive MTC (mMTC) with hybrid non-orthogonal multiple access (NOMA)-orthogonal frequency division multiple access (OFDMA). First, a hybrid multiple access scheme, including the NOMA-based congestion-alleviating access scheme (NCAS) and OFDMA-based congestion-alleviating access scheme (OCAS), is proposed, in which the NOMA based devices coexist with OFDMA based ones. Then, aiming at maximizing the system access capacity, a traffic-aware resource blocks (RBs) allocation is investigated to optimize RBs allocation for preamble transmission and data packets transmission, as well as to optimize the RBs allocation between NCAS and OCAS for the RBs usage efficiency improvement. Next, aiming at the problem of high computational complexity and improving energy efficiency in hybrid NOMA-OFDMA based cellular M2M communications, this paper proposes an improved low complexity power allocation algorithm. The feasibility conditions of power allocation solution under the maximum transmit power constraints and quality of service (QoS) requirements of the devices is investigated. The original non-convex optimization problem is solved under the feasibility conditions by two iterative algorithms. Finally, a device clustering scheme is proposed based on the channel gain difference and feasible condition of power allocation solution, by which NOMA based devices and OFDMA based devices can be determined. Simulation results show that compared with non-orthogonal random access and transmission (NORA-DT), the proposed resource allocation scheme for hybrid NOMA-OFDMA systems can efficiently improve the performance of access capacity and energy efficiency.

A low complexity power allocation scheme for NOMA-based indoor VLC systems

The narrow modulation bandwidth of light emitting diode (LED) is a barrier for indoor visible light communication (VLC) systems to achieve high data rate. The non-orthogonal multiple access (NOMA) is considered to be a promising technology to improve spectral efficiency of wireless communication systems. In this paper, we apply the non-orthogonal multiple access (NOMA) to visible light communication (VLC) systems, and propose a low complexity power allocation scheme for NOMA-based indoor VLC systems which is called the simplified gain ratio power allocation (S-GRPA) scheme. In the S-GRPA scheme, the channel state information (CSI) used for power allocation is not complete and obtained through look-up table method rather than calculation, which reduces the complexity of the power allocation scheme. Simulation results are presented to verify the effectiveness of the proposed scheme.