We consider the problem of rate allocation in a Gaussian multiple-access channel, with the goal of maximizing a utility function over transmission rates. In contrast to the literature which focuses on linear utility functions, we study general concave utility functions. We present a gradient projection algorithm for this problem. Since the constraint set of the problem is described by exponentially many constraints, methods that use exact projections are computationally intractable. Therefore, we develop a new method that uses approximate projections. We use the polymatroid structure of the capacity region to show that the approximate projection can be implemented by a recursive algorithm in time polynomial in the number of users. We further propose another algorithm for implementing the approximate projections using rate-splitting and show improved bounds on its convergence time.
This paper studies the joint user association and resource allocation in heterogeneous networks (HetNets) from a novel perspective, motivated by and generalizing the idea of fractional frequency reuse. By treating the multi-cell multi-user resource allocation as resource partitioning among multiple reuse patterns, we propose a unified framework to analyze and compare a wide range of user association and resource allocation strategies for HetNets, and provide an optimal benchmark for network performance. The enabling mechanisms are a novel formulation to consider all possible interference patte…
The introduction of device-to-device (D2D) into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of user equipments (UEs). In this paper, we propose a distributed interference-aware energy-efficient resource allocation algorithm to maximize each UE's energy efficiency (EE) subject to its specific quality of service (QoS) and maximum transmission power constraints. We model the resource allocation problem as a noncooperative game, in which each player is self-interested and wants to…
In this paper, channel resource allocation problem for LEO mobile satellite systems is investigated and a new dynamic channel resource allocation scheme is proposed based on differential game. Optimal channel resource allocated to each satellite beams are formulated as Nash equilibrium. It is proved that optimal channel resource allocation can be achieved and the differential game based scheme is applicable and acceptable. Numerical results shows that system performance can be improved based on the proposed scheme.
This work presents joint subcarrier, power and bit allocation schemes for multi-user OFDM based overlay cognitive radio under constraints on primary user throughput loss and total secondary user transmitted power. Closed form for expressions for the optimal power and bit allocations are initially derived. Subsequently, optimal and suboptimal algorithms to realise the joint subcarrier, power and bit allocations are introduced. Numerical simulations are used to evaluate the performance of the joint resource allocation algorithms.
The ever-increasing number of nodes in current and future wireless communication networks brings unprecedented challenges for the allocation of the available communication resources. This is caused by the combinatorial nature of the resource allocation problems, which limits the performance of state-of-the-art techniques when the network size increases. In this paper, we take a new direction and investigate how methods from statistical physics can be used to address resource allocation problems in large networks. To this aim, we propose a novel model of the wireless network based on a type of …
In this article, we examine several design and complexity aspects of the optimal physical layer resource allocation problem for a generic interference channel (IC). The latter is a natural model for multi-user communication networks. In particular, we characterize the computational complexity, the convexity as well as the duality of the optimal resource allocation problem. Moreover, we summarize various existing algorithms for resource allocation and discuss their complexity and performance tradeoff. We also mention various open research problems throughout the article.
Resource allocation is of great importance in the next generation wireless communication systems, especially for cognitive radio networks (CRNs). Many resource allocation strategies have been proposed to optimize the performance of CRNs. However, it is challenging to implement these strategies and achieve real-time performance in wireless systems since most of them need accurate and timely channel state information and/or other network statistics. In this paper a resource allocation strategy based on deep neural networks (DNN) is proposed and the training method is presented to train the neura…
Device to Device (D2D) communication takes advantage of the proximity between the communicating devices in order to achieve efficient resource utilization, improved throughput and energy efficiency, simultaneous serviceability and reduced latency. One of the main characteristics of D2D communication is reuse of the frequency resource in order to improve spectral efficiency of the system. Nevertheless, frequency reuse introduces significantly high interference levels thus necessitating efficient resource allocation algorithms that can enable simultaneous communication sessions through effective…
In a companion paper, we characterized the optimal resource allocation in terms of power control and subcarrier assignment, for a downlink sectorized OFDMA system. In our model, the network is assumed to be one dimensional for the sake of analysis. We also assume that a certain part of the available bandwidth is likely to be reused by different base stations while that the other part of the bandwidth is shared in an orthogonal way between these base stations. The optimal resource allocation characterized in Part I is obtained by minimizing the total power spent by the network under the constra…
In this pair of papers (Part I and Part II in this issue), we investigate the issue of power control and subcarrier assignment in a sectorized two-cell downlink OFDMA system impaired by multicell interference. As recommended for WiMAX, we assume that the first part of the available bandwidth is likely to be reused by different base stations (and is thus subject to multicell interference) and that the second part of the bandwidth is shared in an orthogonal way between the different base stations (and is thus protected from multicell interference). Although the problem of multicell resource allo…
In this paper, we study the problem of Quality of Experience (QoE) aware resource allocation in wireless systems. In particular, we consider application-aware joint Bandwidth-Power allocation for a small cell. We optimize a QoE metric for multi-user video streaming in a small cell that maintains a trade-off between maximizing the playback rate of each user and ensuring proportional fairness (PF) among users. We formulate the application-driven joint bandwidth-power allocation as a non-convex optimization problem. However, we develop a polynomial complexity algorithm, and we show that the propo…
In this letter, we investigate the resource allocation for downlink multi-cell coordinated OFDMA wireless networks, in which power allocation and subcarrier scheduling are jointly optimized. Aiming at maximizing the weighted sum of the minimal user rates (WSMR) of coordinated cells under individual power constraints at each base station, an effective distributed resource allocation algorithm using a modified decomposition method is proposed, which is suitable by practical implementation due to its low complexity and fast convergence speed. Simulation results demonstrate that the proposed decen…
This paper considers the joint power control and resource allocation for a device-to-device (D2D) underlay cellular system with a multi-antenna BS employing ADCs with different resolutions. We propose a four-step algorithm that optimizes the ADC resolution profile at the base station (BS) to reduce the energy consumption and perform joint power control and resource allocation of D2D communication users (DUEs) and cellular users (CUEs) to improve the D2D reliability.
In this paper, we investigate resource allocation algorithm design for full-duplex (FD) cognitive radio systems. The secondary network employs a FD base station for serving multiple half-duplex downlink and uplink users simultaneously. We study the resource allocation design for minimizing the maximum interference leakage to primary users while providing quality of service for secondary users. The imperfectness of the channel state information of the primary users is taken into account for robust resource allocation algorithm design. The algorithm design is formulated as a non-convex optimizat…
We propose a cross-layer strategy for resource allocation between spatially correlated sources in the uplink of multi-cell FDMA networks. Our objective is to find the optimum power and channel to sources, in order to minimize the maximum distortion achieved by any source in the network. Given that the network is multi-cell, the inter-cell interference must also be taken into consideration. This resource allocation problem is NP-hard and the optimal solution can only be found by exhaustive search over the entire solution space, which is not computationally feasible. We propose a three step meth…
In this paper, we design a resource allocation framework for the delay-sensitive Multi-User MIMO (MU-MIMO) broadcast system with limited feedback. Considering the scarcity and interrelation of the transmit power and feedback bandwidth, it is imperative to optimize the two resources in a joint and efficient manner while meeting the delay-QoS requirement. Based on the effective bandwidth theory, we first obtain a closed-form expression of average violation probability with respect to a given delay requirement as a function of transmit power and codebook size of feedback channel. By minimizing th…
When the future achievable rate is perfectly known, predictive resource allocation can provide high performance gain over traditional resource allocation for the traffic without stringent delay requirement. However, future channel information is hard to obtain in wireless channels, especially the small-scale fading gains. In this paper, we analytically demonstrate that the future large-scale channel information can capture almost all the performance gain from knowing the future channel by taking an energy-saving resource allocation as an example. This result is important for practical systems,…
In this paper, we study resource allocation for downlink orthogonal frequency division multiple access (OFDMA) systems with the objective to enable ultra-reliable low latency communication (URLLC). To meet the stringent delay requirements of URLLC, the impact of short packet communication is taken into account for resource allocation algorithm design. In particular, the resource allocation design is formulated as a weighted system sum throughput maximization problem with quality-of-service (QoS) constraints for the URLLC users. The formulated problem is non-convex, and hence, finding the globa…
This paper studies the allocation of shared resources between vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) links in vehicle-to-everything (V2X) communications. In existing algorithms, dynamic vehicular environments and quantization of continuous power become the bottlenecks for providing an effective and timely resource allocation policy. In this paper, we develop two algorithms to deal with these difficulties. First, we propose a deep reinforcement learning (DRL)-based resource allocation algorithm to improve the performance of both V2I and V2V links. Specifically, the algorit…
This paper considers the resource allocation algorithm design for downlink multiple-input single-output (MISO) orthogonal frequency division multiple access (OFDMA) ultra-reliable low latency communication (URLLC) systems. To meet the stringent delay requirements of URLLC, short packet transmission is adopted and taken into account for resource allocation algorithm design. The resource allocation is optimized for maximization of the weighted system sum throughput subject to quality-of-service (QoS) constraints regarding the URLLC users' number of transmitted bits, packet error probability, and…
In this paper, joint resource allocation and power control for energy efficient device-to-device (D2D) communications underlaying cellular networks are investigated. The resource and power are optimized for maximization of the energy efficiency (EE) of D2D communications. Exploiting the properties of fractional programming, we transform the original nonconvex optimization problem in fractional form into an equivalent optimization problem in subtractive form. Then, an efficient iterative resource allocation and power control scheme is proposed. In each iteration, part of the constraints of the …
In this paper, we study the power-efficient resource allocation for multicarrier non-orthogonal multiple access (MC-NOMA) systems. The resource allocation algorithm design is formulated as a non-convex optimization problem which takes into account the statistical channel state information at transmitter and quality of service (QoS) constraints. To strike a balance between system performance and computational complexity, we propose a suboptimal power allocation and user scheduling with low computational complexity to minimize the total power consumption. The proposed design exploits the heterog…
This paper studies interference alignment (IA) based multi-cell cooperative resource allocation for the downlink OFDMA with universal frequency reuse. Unlike the traditional scheme that treats subcarriers as separate dimensions for resource allocation, the IA technique is utilized to enable frequency-domain precoding over parallel subcarriers. In this paper, the joint optimization of frequency-domain precoding via IA, subcarrier user selection and power allocation is investigated for a cooperative three-cell OFDMA system to maximize the downlink throughput. Numerical results for a simplified s…
In this paper, we study power-efficient resource allocation for multicarrier non-orthogonal multiple access (MC-NOMA) systems. The resource allocation algorithm design is formulated as a non-convex optimization problem which jointly designs the power allocation, rate allocation, user scheduling, and successive interference cancellation (SIC) decoding policy for minimizing the total transmit power. The proposed framework takes into account the imperfection of channel state information at transmitter (CSIT) and quality of service (QoS) requirements of users. To facilitate the design of optimal S…
As a promising paradigm for the fifth generation wireless communication (5G) system, the fog radio access network (F-RAN) has been proposed as an advanced socially-aware mobile networking architecture to provide high spectral efficiency (SE) while maintaining high energy efficiency (EE) and low latency. Recent advents are advocated to the performance analysis and radio resource allocation, both of which are fundamental issues to make F-RANs successfully rollout. This article comprehensively summarizes the recent advances of the performance analysis and radio resource allocation in F-RANs. Part…
We study resource allocation algorithm design for energy-efficient communication in an OFDMA downlink network with hybrid energy harvesting base station. Specifically, an energy harvester and a constant energy source driven by a non-renewable resource are used for supplying the energy required for system operation. We first consider a deterministic offline system setting. In particular, assuming availability of non-causal knowledge about energy arrivals and channel gains, an offline resource allocation problem is formulated as a non-convex optimization problem taking into account the circuit e…
Intel Labs（英特尔实验室）；Georgia Institute of Technology（佐治亚理工学院）；Zhejiang University（浙江大学）
It has been a long-held belief that judicious resource allocation is critical to mitigating interference, improving network efficiency, and ultimately optimizing wireless communication performance. The traditional wisdom is to explicitly formulate resource allocation as an optimization problem and then exploit mathematical programming to solve the problem to a certain level of optimality. Nonetheless, as wireless networks become increasingly diverse and complex, e.g., in the high-mobility vehicular networks, the current design methodologies face significant challenges and thus call for rethink…
In this paper, we consider a single-cell multi-user orthogonal frequency division multiple access (OFDMA) network with one unmanned aerial vehicle (UAV), which works as an amplify-and-forward relay to improve the quality-of-service (QoS) of the user equipments (UEs) in the cell edge. Aiming to improve the throughput while guaranteeing the user fairness, we jointly optimize the communication mode, subchannel allocation, power allocation, and UAV trajectory, which is an NP-hard problem. To design the UAV trajectory and resource allocation efficiently, we first decompose the problem into three su…
This paper addresses join wireless and computing resource allocation in mobile edge computing (MEC) systems with several access points and with the possibility that users connect to many access points, and utilize the computation capability of many servers at the same time. The problem of sum transmission energy minimization under response time constraints is considered. It is proved, that the optimization problem is non-convex. The complexity of optimization of a part of the system parameters is investigated, and based on these results an Iterative Resource Allocation procedure is proposed, t…
