Improved Sum Rate Research Articles

Optimization of a two‐color reuse scheme in multi‐beam high throughput satellite systems

AbstractIn this letter, we propose a two‐color reuse scheme in the forward link of multi‐beam high throughput satellite systems, where dual‐polarization is utilized to provide an additional dimension to isolate severe inter‐beam interference. This scheme is optimized through formulating a nonconvex optimization problem with respect to precoding design to maximize system sum rate, taking into account the intense interference among beams using the same polarization. Then a path‐following algorithm is proposed for its solution. Afterwards, we further seek a low‐complexity precoding design and simplify the original precoding optimization problem into a power allocation one, whose problem is still non‐convex and a quadratic transform algorithm is proposed to achieve its near‐optimum. Extensive simulations verify that the proposed scheme exhibits improved sum rate, compared to that of the current single polarization full frequency reuse and four‐color frequency reuse ones.

Green Rate‐Splitting Multiple Access for Multicell and Rate Fairness Maximization

ABSTRACTThis paper investigates the green design of rate‐splitting multiple access (RSMA) for multicell, multiantenna downlink communication systems to maximize rate fairness under quality of service (QoS) constraints. An optimization framework is developed to minimize the weighted sum power consumption by jointly optimizing transmit beamformers, power allocation, and common/private rate split while ensuring per‐user minimum rate requirements. The algorithm design explicitly considers the rate fairness among users via a newly proposed green fairness index. The nonconvex transceiver design problems are transformed into tractable forms and efficiently solved by applying tools from alternating optimization and successive convex approximation. Extensive simulations demonstrate that the proposed green RSMA optimization framework can effectively balance the throughput among cell‐edge and cell‐center users, hence combating the near‐far effect. Simulation results show that at 20‐dB SNR, green RSMA achieves over 20% and 50% sum rate improvement compared with NOMA and OMA, respectively. Moreover, green RSMA maintains high fairness among users, even when the channel conditions are disparate. When the weakest user is located 120 m from the base station, green RSMA exhibits a 21.2% higher fairness index than NOMA, showcasing its ability to ensure equitable service quality across users. The framework also achieves substantial energy efficiency gains, consuming less power while providing higher data rates than baseline schemes. These results demonstrate the effectiveness of green RSMA in enhancing spectral efficiency, user fairness, and energy efficiency in multicell, multiantenna communication systems, making it a promising solution for sustainable and high‐performance wireless networks.

An efficient algorithm for resource optimization in IRS-mmWave-NOMA B5G wireless networks

An efficient algorithm for resource optimization in IRS-mmWave-NOMA B5G wireless networks

STAR-RIS-Enabled Short-Packet NOMA Systems

This paper analyzes the performance of simultaneous transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS)-enabled short-packet non-orthogonal multiple access (NOMA) systems. A mode-switching protocol combined with partition strategies (MSPS) for the STAR-RIS design is proposed to simultaneously serve multiple actuators along with the discrete phase-shift alignment in order to reduce the STAR-RIS implementation costs. Approximate and asymptotic closed-form expressions for the average block error rate (BLER) and achievable rate have been derived to reveal some useful insights, such as the actuators' diversity order, coding gain, the power allocation factor, packet length, and the number of information bits. Numerical results confirm that: i) the considered system achieves better BLER balance among the actuators than classical RIS-based short-packet NOMA systems and higher achievable sum rate than RIS-based short-packet orthogonal multiple access ones; ii) the STAR-RIS with discrete phase shift design using 3-bit quantization achieves near-optimal performance with the continuous phase shift; iii) there is a trade-off between using bit quantizer and the total number of STAR-RIS elements; and iv) the power allocation strategy provides better average sum rate improvement than block-length increasing strategy.

Phase and 3-D Placement Optimization for Rate Enhancement in RIS-Assisted UAV Networks

In this letter, we aim at improving the system sum-rate performance of an assisted aerial base station (ABS) network by considering use of reconfigurable intelligent surface (RIS). We jointly optimize the RIS phase shifts and ABS altitudes using the proposed conjugate gradient and particle swarm optimization (CG-PSO) scheme. Moreover, we divide the problem into sub-problems and solve them using an alternative optimization method. First, an optimal RIS phase shift is computed using the conjugate gradient (CG) under the fixed ABS altitude and varying transmit power. Finally, we find the optimal ABS altitude using particle swarm optimization (PSO), which results in improved sum rate under the optimized RIS phase shift. The results show that the CG-PSO scheme significantly improves the system sum rate compared to the baseline schemes.

Sum Rate Maximization for Active RIS-Aided Uplink Multi-Antenna NOMA Systems

Both reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA) are treated as promising technologies for future wireless communications. However, the performance gain achieved by the traditional passive RIS-aided NOMA system is limited due to the double-fading effect for the base station (BS)-RIS-user channel. In this letter, a sum rate maximization problem for active RIS-aided uplink multi-antenna NOMA system is studied, in which the reflecting elements (REs) of active RIS can manipulate the phase shifts and amplify the amplitudes of incident signals. To tackle the formulated sum rate maximization problem, the original optimization problem is decomposed into three subproblems, i.e., the equalizer optimization, the power allocation, and the active RIS beamforming design. Simulation results show that the proposed active RIS-aided NOMA system can effectively improve sum rate compared with several benchmark schemes.

Energy Constrained Sum-Rate Maximization in IRS-Assisted UAV Networks With Imperfect Channel Information

The focus of this work is maximizing the sum-rate of wireless unmanned aerial vehicle (UAV) networks with intelligent reflecting surfaces (IRS) in the presence of system practical limitations. More specifically, we consider that the phase compensation at the IRS is imperfect due to various factors such as device imperfections and channel estimation errors. Moreover, we consider that the IRS elements have limited switching frequency, which limits the possibility of being allocated to different UAVs over consecutive time slots when time-division multiple access (TDMA) is considered. To this end, we formulate an optimization problem where the objective is to maximize the network sum-rate subject to total energy and quality-of-service (QoS) constraints by optimizing the number of IRS elements and power allocated to each UAV. To solve the optimization problem, a low-complexity heuristic algorithm is proposed based on the quality of the estimated phase for each IRS element. The proposed approach is compared to benchmark techniques such as the uniform allocation process and genetic algorithm. The obtained results show that a significant sum-rate improvement of up to 45% can be gained using the proposed algorithm.

Power Allocation for IRS-Aided Two-Way Decode-and-Forward Relay Wireless Network

In this paper, an intelligent reflecting surface (IRS)-aided two-way decode-and-forward (DF) relay wireless network is considered, where two users exchange information via IRS and DF relay. To enhance the sum rate performance, three power allocation (PA) strategies are proposed. Firstly, a maximizing sum rate method based on successive convex approximation (Max-SR-SCA) is proposed to jointly optimize the PA factors of user1 ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$U_{1}$</tex-math></inline-formula> ), user2 ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$U_{2}$</tex-math></inline-formula> ) and relay station (RS). To further improve sum rate performance, a method of maximizing determinant (Max-Det) with a higher sum rate enhancement is presented. Considering the asymmetry of two-way rates caused by channel quality and two users' demand, maximizing sum rate with rate constraint (Max-SR-RC) is put forward. Simulation results show that the proposed three PA methods not only outperform the equal power allocation (EPA) method, but also the sum rates corresponding to the three PA methods are slightly lower than that of optimal exhaustive search (ES) method. Especially for Max-SR-RC method, its rate gain over EPA is up to 64.7% and its sum rate gap with optimal ES is less than 0.1bits/s/Hz. Furthermore, it is verified that the total power and random shadow variable <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$X_\sigma$</tex-math></inline-formula> have a substantial impact on the sum rate.

Sum Rate Maximization of MIMO Monostatic Backscatter Networks by Suppressing Residual Self-Interference

Monostatic backscatter (MBS) networks provide connectivity for ultra-low power and low-cost tags for numerous applications. However, the reader operates in the full-duplex (FD) mode and experiences self-interference (SI) levels much higher (e.g., 160 dB) than the desired signal. However, hardware-based SI cancellation (SIC) techniques can remove SI partially only. Therefore, residual SI (RSI) dramatically degrades system performance. To remedy this problem, we develop a sum-rate maximization algorithm that suppresses the RSI and ensures that the tags harvest sufficient energy. It jointly optimizes the reader precoder and combiners and the tags reflection coefficients. Because of the non-convexity of this problem, we utilize alternating optimization (AO) to split it into three parts. They are then solved using successive convex approximation (SCA) and semidefinite relaxation (SDR) techniques to yield the precoder, a generalized Rayleigh quotient-based closed-form solution for the combiners, and geometric programming (GP) to get the reflection coefficients. Simulation results validate the fast convergence of the algorithm and show significant sum rate improvements (more than 21%) over the baselines.

Multi-Pair Computation for C-RAN With Intra-Cloud and Inter-Cloud Communications

Most existing works on cloud radio access networks (C-RAN) design uplink or downlink transmission schemes separately. However, joint uplink and downlink transmission scheme design may offer additional benefits, especially in C-RANs with intra-cloud communications. In this letter, a multi-pair computation based transmission scheme is proposed for C-RANs with combined intra-cloud and inter-cloud communications, where the uplink and downlink are designed jointly while taking into account message source-destination information. The achievable rates are derived, optimized, and evaluated numerically under limited fronthaul capacity and quality of service (QoS) constraints. Simulation results reveal significant sum rate improvements compared to the state-of-the-art.

Exploring Sum Rate Maximization in UAV-Based Multi-IRS Networks: IRS Association, UAV Altitude, and Phase Shift Design

This paper studies the unmanned aerial vehicle (UAV) based multiple intelligent reflecting surface (IRS) network, where the hovering UAV acts as a base station, and the IRS enhances signal transmission to across obstacle between users and UAV. To achieve the maximum sum rate of proposed communication scenario, a non-convex problem considering IRS association results, hovering altitude of UAV, and the phase shift design of multi-IRS is formulated. From the IRS association problem, we can find that the IRS association results are coupled to the decoding order of non-orthogonal multiple access (NOMA). To tackle this, a mathematical interference expansion scheme is developed to decouple it and transform it to convex by binary relaxation method. The non-convexity of hovering altitude optimization problem is solved by logarithm operation, approximation, and auxiliary matrices. For the phase shift optimization problem of multi-IRS, we propose a gradient approximation based initial scheme and develop a univariate optimization based approach on the basis to achieve the users sum rate improvement in multi-IRS. In the end, we compare the proposed scheme with baseline scheme to present the superiority of this work under various network settings. The internal reasons for the variation of simulation results are also analyzed.

Reinforcement Learning-Based Dynamic Anti-Jamming Power Control in UAV Networks: An Effective Jamming Signal Strength Based Approach

Unmanned aerial vehicle (UAV) assisted air-to-ground (A2G) communication is vulnerable to malicious jamming due to the broadcast nature of wireless communications. In this letter, an anti-jamming power control framework with an unknown jamming model and unknown transmission power is proposed. In particular, the probability density function (PDF) of the effective jamming signal strength (EJSS) is first estimated via kernel density estimation (KDE). Then, utilizing the EJSS, a deep deterministic policy gradient (DDPG) based framework is proposed to acquire the power control strategy in real time. Moreover, a trajectory design scheme based on K-means++ is proposed to track the location of users. The simulation results show that the proposed framework yields an improved sum rate and energy efficiency over the reference schemes.

Ефективність системи трисотової мережі для граничних користувачів з використанням попереднього кодування, регулювання завади і зворотним зв’язком квантованого обмеженого каналу

Користувачі на загальній границі багатокористувацької трисотової MIMO системи з низхідною лінією зв’язку страждають від низької потужності сигналу у власній соті, а також від сигналу завад рівної потужності від сусідніх двох сот. В даному випадку для покращення загальної роботи системи застосовуються схеми придушення завад. Крім того, повний CSI зворотний зв’язок від користувачів до базової станції сильно навантажує канал зворотного зв’язку. Зворотний зв’язок інформаційного квантованого редукованого каналу може зменшити навантаження майже наполовину на зворотний канал від користувача до передавача, та підвищити швидкість передачі даних системи. Методи попереднього кодування на основі кодової книги LTE покращують сумарну швидкість. Розроблено метод попереднього кодування з використанням сингулярного розкладання SVD (singular value decomposition) на вибраних кодових векторах на основі максимізації вектору еквівалентного коду каналу SVD-ECC (SVD Equivalent Channel-Code) і максимізації вектору SINR-коду SVD-SINRC (SVD SINR-Code). Обидва методи забезпечують вищу сумарну швидкість передачі даних системи в порівнянні з методом попереднього кодування на основі ZF (zero forcing), причому швидкість більша для SVD-ECC, ніж для SVD-SINRC. Також проведено дослідження для користувачів з ортогональними еквівалентними каналами та подальшим SVD на вибраному каналі користувача SVD-ORT (SVD orthogonal). Отримано результати зі зміною SNR користувача, кількості вибраних користувачів K і загальної кількості активних користувачів L у соті.

The Optimal Power Allocation for Sum Rate and Energy Efficiency of Full-Duplex Two-Way Communication Network.

Full-duplex (FD) transmission holds a great potential of improving the sum data rate of wireless communication systems. However, the self-interference introduced by the full-duplex transmitter brings a big challenge to enhance the energy efficiency. This paper investigates the power allocation problem in a full-duplex two-way (FDTW) communication network over an OFDM channel, aiming at improving the sum data rate and energy efficiency. We first characterize the sum rate and energy efficiency achieved in a single-carrier FDTW system. The optimal transmit power that achieves the maximal sum data rate is presented. The energy efficiency maximization problem is solved by using fractional programming. Then we further formulate sum rate and energy efficiency maximization problem in a multi-subcarrier FDTW system. In particular, the sub-optimal transmit power allocation which achieves a decent sum rate improvement is found by using a proposed iterative algorithm. By combining the iterative algorithm and fractional programming, we further maximize the energy efficiency of the multi-subcarrier system. With our proposed algorithm, we can easily obtain an optimal transmit power that approximates the global optimal solution. Simulation results show that using the obtained optimal transmit power allocation algorithm can significantly improve the sum rate and energy efficiency in both single-carrier and multi-subcarrier systems.

3D UAV Trajectory and Data Collection Optimisation Via Deep Reinforcement Learning

Unmanned aerial vehicles (UAVs) are now beginning to be deployed for enhancing the network performance and coverage in wireless communication. However, due to the limitation of their on- board power and flight time, it is challenging to obtain an optimal resource allocation scheme for the UAV-assisted Internet of Things (IoT). In this paper, we design a new UAV-assisted IoT system relying on the shortest flight path of the UAVs while maximising the amount of data collected from IoT devices. Then, a deep reinforcement learning-based technique is conceived for finding the optimal trajectory and throughput in a specific coverage area. After training, the UAV has the ability to autonomously collect all the data from user nodes at a significant total sum-rate improvement while minimising the associated resources used. Numerical results are provided to highlight how our techniques strike a balance between the throughput attained, trajectory, and the time spent. More explicitly, we characterise the attainable performance in terms of the UAV trajectory, the expected reward and the total sum-rate.

Successive interference cancellation and alignment in K-user MIMO interference channels with partial unidirectional strong interference

Recently cellular networks have been densely and heterogeneously deployed indoors and outdoors to expand the network capacity, and thus the in-building propagation loss and the transmit power diversity of access points will exacerbate link heterogeneity and result in partial unidirectional strong interference. To make full use of the strong interference feature, we propose the successive interference cancellation and alignment (SICA) scheme in the K-user interference channel with partial unidirectional strong interference. SICA is designed to transmit two kinds of data streams simultaneously, the alignment streams and superposition streams. The alignment streams will follow the interference alignment criterion to maintain the optimal degrees of freedom (DoF) performance; the superposition streams are handled via successive interference cancellation at all the strongly interfered receivers to improve the overall achievable rate. The joint transceiver designs for SICA is modeled as a weighted sum rate (WSR) maximization problem, and then can be alternately solved for a local optimum according to the optimality equivalence between WSR and its corresponding weighted mean square error (WMMSE) problem. Simulation results have confirmed the sum rate improvement and DoF optimality of the proposed SICA scheme.

A Study on Improved Sum Rate of Cross-Correlated SC NOMA toward 6G URLLC

Since recently only an auto-correlated superposition coding (SC) scheme for non-orthogonal multiple access(NOMA) has been investigated, this paper proposes a cross-correlated SC scheme for NOMA. First, we derive the closed-form expression of the sum rate of the proposed cross-correlated SC scheme. Then, numerical analyses demonstrate that the sum rate of the proposed cross-correlated SC scheme is larger than that of the conventional auto-correlated SC scheme. We also show that for the stronger channel gain user, the signal-to-noise ratio (SNR) gain of the proposed cross-correlated SC scheme is about 15, compared with the conventional auto-correlated SC scheme. As a result, the proposed cross-correlated SC scheme could be a promising technology for 6G ultra-reliable low-latency communications (URLLC).

Sum-Rate Improvement in Massive MIMO System with User Grouping and Selection, and Antenna Scheduling Scheme

In this paper, we have proposed user grouping method and new user selection techniques in TDD Massive (MIMO) systems. Using K-means clustering algorithm we separate the users into different groups. Upon user groups are formed users are selected from different groups with Semi-Orthogonal (SO) and random user selection criteria. We use two user selection method to select users from different groups, those are-(i) Users are selected in intra-group those are SO with each other along with it also SO with other group’s users, (ii)-Users are selected from inter-group those are SO with each other. For antenna scheduling we used maximum channel gain measure in both the user selection situation. Semi-Orthogonal user selection (SOU) and antenna scheduling with zero forcing precoding demonstrated maximum system sum-rate that is seen in results. In table-1 appraised the computational cost of our modified SOU algorithm. The proposed algorithm’s efficiency is explored through the simulations.

Opportunistic Beamforming Using an Intelligent Reflecting Surface Without Instantaneous CSI

While intelligent reflecting surface (IRS) assisted wireless communication has emerged as an important research paradigm, channel state information (CSI) acquisition remains a critical challenge to design the IRS phase-shifts and yield the promised coherent beamforming gains. In this letter, we propose an IRS-assisted opportunistic beamforming (OBF) scheme under proportional fair scheduling, which does not require instantaneous CSI to design the IRS parameters. In a slow-fading environment, we show that with only random rotations at the IRS, the proposed scheme can capitalize on the multi-user (MU)-diversity effect to approach the performance of coherent beamforming as the number of users grows large. Next we study the sum-rate scaling of IRS-assisted OBF in the correlated Rayleigh fast fading environment under a deterministic beamforming scheme that results in a considerable sum-rate improvement.

Interference alignment and scheduling in clustered partially connected small cell networks

SummaryInterference alignment (IA) is a beneficial interference management technique in heterogeneous networks (HetNets). Bearing this in mind, we target partially connected networks of small cells that are allocated randomly in a macrocell, whereas IA feasibility conditions may not be satisfied. To address this issue, we propose a new scheme with novel clustering and scheduling algorithms that is accomplished in three stages. The proposed scheme is accomplished by knowing the connection matrix of the established links that is obtained by different threshold values in the first stage. In the second stage, a new clustering algorithm is proposed to separate the cells to groups in which IA is feasible, and the feedback overhead is reduced. In the last stage, cluster scheduling method is proposed to efficiently schedule the clusters. The cluster scheduling allows the selected clusters with trivial intercluster interferences to transmit at the same time slot. The simulation results indicate the improvement of achievable averaged sum rate by the proposed clustering and cluster scheduling.