Joint Optimal Resource Allocation Research Articles

Joint Optimization for Pedestrian, Information and Energy Flows in Emergency Response Systems With Energy Harvesting and Energy Sharing

The rapid progress in informatisation and electrification in transportation has gradually transferred public transport junctions such as metro stations into the nexus of pedestrian flows, information flows, computation flows and energy flows. These smart environments that are efficient in handling large volume passenger flows in routine circumstances can become even more vulnerable during emergency situations and amplify the losses in lives and property owing to power outage triggered service degradation and destructive crowed behaviours. On the bright side, the increasingly abundant resources contained in smart environments have enlarged the optimisation space of an evacuation process, yet little research has concentrated on the joint optimal resource allocation between transportation infrastructures and pedestrians. Hence, in the paper, we propose a queueing network based resource allocation model to comprehensively optimise various types of resources during emergency evacuations. Experiments are conducted in a simulated metro station environment with realistic settings. The simulation results show that the proposed model can considerably improve the evacuation efficiency as well as the robustness of the emergency response system during emergency situations.

Power Minimization in Dual-Hop Underlay Cooperative Cognitive Radio Relay Networks for Optimal Resource Allocation

In this paper, we investigate a multi-user one-way dual-hop multi-relay cognitive radio underlay spectrum sharing network. .The joint optimal resource allocation of the bandwidth and power allocation in underlay Cooperative Cognitive Radio Relay Network (CCRRN) was studied and a convex optimization analytical framework is presented. A combined optimal power and bandwidth allocation (COPBA) scheme for the minimization of the total network power and blocking probability of the call admission control stage of the CCRRN is investigated. Our goal is to jointly optimize the bandwidth and power allocation such that the total transmission power in the CCRRN is minimized without compromising the Quality of Service (QoS) demands of the secondary users (SUs) and the interference constraint thresholds of the primary users (PUs) in the primary networks. The mathematical model and convex optimization problem with the aim of minimizing the total transmission power of the CCRRN was formulated. The resulting optimization problem was solved in the standard computer based numerical optimization solver package CONOPT in MATLAB/TOMLAB environment. Simulation results obtained is compared the equal-bandwidth optimal power allocation scheme. Keywords—Radio resource allocations; Cognitive radio Networks; Convex optimization; Cooperative relay networks, Transmit power minimization

Novel Cooperative Scheme Based on Joint Band Assignment and Power Allocation for a Coexisting Radar-Communications System.

In this paper, we present a novel cooperative scheme of joint optimal resource allocation, such that the overall performance of the coexisting radar-communications (CRC) system can be improved. In our proposed scheme, target detection and multiuser communication are performed by radar and communication subsystems at the same time, as well as a control center, which is responsible for joint resource management. We aim to minimize the ISLR for target detection and maximize the sum-rate for communications simultaneously by jointly optimizing the band assignment and transmit power allocation. Since the resulting optimization problem involving two performance metrics and a binary constraint is a multiobjective nonconvex problem, a two-tier iterative decomposition (TT-ID) approach is devised to obtain the globally optimal solution. However, compared with the conventional radar signals, the autocorrelation function of the devised radar signal may still have relatively high sidelobes. In particular, when the data transmission becomes the primary purpose of the CRC system, the sidelobe performance gets worse. As a consequence, some weak targets are most likely overshadowed by the adjacent strong targets through the matched filtering at the radar receiver. To address this, a spectral estimation algorithm based on the Bayes Cauchy–Gaussian (Bayes–CG) model is employed to further reduce the range sidelobes of the matched filter output at the radar receiver according to the prior distribution of the desired autocorrelation. Finally, several numerical results are provided to show the merits of the proposed method.

Joint optimal resource allocation schemes for downlink cooperative cellular networks over orthogonal frequency division multiplexing carriers

This study concentrates on the study of a downlink cooperative cellular (DCC) network in which an access point is located in the centre of each cell and two relay stations are installed in the border between both sectors of a cell to obtain higher cell-edge throughput. To optimise the network efficiency, a joint optimal subcarrier and power allocation scheme is proposed which initially derives the highest achievable rate for a single-legacy user (LU), then, through further evaluation and analysis, this is generalised to the case of a multiple-LU environment. Next, to maximise the overall throughput and ensure fairness, a multi-objective lexicographical optimisation problem (MLOP) is formulated to maximise the minimum LUs rate while improving the overall throughput. As the proposed MLOP is a mixed-integer non-linear problem, finding optimal solutions is impractical and in general, there is no standard method for optimally obtaining a solution. Hence, two efficient algorithms are introduced in this study. Simulation results confirm that the proposed algorithms achieve a fair and near-optimal performance for the multi-LU DCC network based on two relay channels, which makes them desirable in practice compared to some of the sub-optimal well-known algorithms investigated in this study.

Joint Resource Allocation, Placement and User Association of Multiple UAV-Mounted Base Stations With In-Band Wireless Backhaul

The in-band wireless backhaul that shares spectrum resources between fronthaul and backhaul is a promising method for unmanned aerial vehicle-mounted base stations (UBSs) to provide wireless services with limited resources. However, the existing works mainly considered the out-band wireless backhaul, where the resources of fronthaul and backhaul are allocated separately. Moreover, the UBS placement methods usually focused on the optimization of fronthaul while neglecting the backhaul. In this letter, a placement algorithm that jointly optimizes the resource allocation and user association for multiple UBSs with in-band wireless backhaul is proposed. In particular, the joint optimal resource allocation for both fronthaul and backhaul is derived using convex optimization theory. Given the optimal resource allocation, an equivalent spectrum efficiency is defined to simplify the optimization problem. As a result, an effective algorithm is proposed by solving the user association problem and UBS placement problem iteratively. In addition, simulation results are provided to verify the efficiency and effectiveness of our proposed method.

Heterogeneous Networks Relying on Full-Duplex Relays and Mobility-Aware Probabilistic Caching

Joint optimal resource allocation and probabilistic caching design is conceived for device-to-device (D2D) communications in a heterogeneous wireless network (HetNet) relying on full-duplex (FD) relays. In particular, popular contents can be cached at user devices and at relays that are located close to users. A user may request the contents of interest from another user via D2D communications and also from a nearby relay equipped with FD radios. If the requested contents are not found in the buffers of other users/relays within the coverage range, users may opt for connecting to the macro base station (MBS) via a relay by using an FD communication. Furthermore, we propose a beneficial mobility-aware coded caching philosophy for D2D communications in the HetNet considered. Especially, we model the mobility pattern of users as discrete random jumps and exploit coded caching for improving the throughput attained. Subsequently, we develop mathematical models for analyzing the throughput in the presence of edge caching, where both the system-level co-channel interference and the FD self-interference are considered. We circumvent the high complexity of stochastic optimization by developing low-complexity optimization. Finally, numerical results are presented to illustrate the theoretical findings developed in this paper and quantify the throughput gains attained.

D2D Communications in Heterogeneous Networks With Full-Duplex Relays and Edge Caching

This paper studies the joint optimal resource allocation and probabilistic caching design for device-to-device (D2D) communications in a wireless heterogeneous network with full-duplex (FD) relays. In particular, popular contents can be cached at user devices as well as at relays that are located close to users. A user can request contents from another user via D2D communications and also from a nearby relay equipped with FD radios. In the case that there is a caching miss (i.e., the requested contents are not found at the other users/relays within the coverage range), users can connect to the base station via a relay by using the FD communication technology. Subsequently, we develop mathematical models to analyze the throughput performance with edge caching where both cochannel system level interference and FD self-interference are considered. Due to the high complexity of stochastic optimization, we develop low-complexity optimization formulation by decomposing the original problem into three simple subproblems that can be efficiently solved. Finally, numerical results are presented to illustrate developed theoretical findings in the paper and significant performance gains of the throughput performance.

Video Multicast With Joint Resource Allocation and Adaptive Modulation and Coding in 4G Networks

Although wireless broadband technologies have evolved significantly over the past decade, they are still insufficient to support the fast-growing mobile traffic, especially due to the increasing popularity of mobile video applications. Wireless multicast, aiming to exploit the wireless broadcast advantage, is a viable approach to bridge the gap between the limited wireless capacity and the ever-increasing mobile video traffic demand. In this paper, we propose MuVi, a Multicast Video delivery scheme through joint optimal resource allocation and adaptive modulation and coding scheme in OFDMA-based 4G cellular networks. MuVi differentiates video frames based on their importance in reconstructing the video and incorporates an efficient radio resource allocation algorithm to optimize the overall video quality across all users in the multicast group. MuVi is a lightweight solution with most of the implementation in the gateway, slight modification in the base station, and no modification at the clients. We implement MuVi on a WiMAX testbed and compare its performance to a Naive wireless multicast scheme that employs the most robust Modulation and Coding Scheme (MCS), and an Adaptive scheme that employs the highest MCS supportable by all clients. Experimental results show that MuVi improves the average video peak signal-to-noise ratio (PSNR) by up to 13 and 7 dB compared to the Naive and the Adaptive schemes, respectively. MuVi does not require modification to the video encoding scheme or the air interface. Thus, it allows speedy deployment in existing systems.

Joint Optimal Resource Allocation and PAPR Reduction Algorithm for OFDMA Systems

One of the drawbacks of an orthogonal frequency division multiplexing (OFDM) system is the larger peak to averaged power ratio (PAPR). The PAPR reduction scheme is a complicated problem, especially when a resource allocation is considered jointly. In this paper, a joint algorithm for determining an optimal resource allocation with PAPR awareness is proposed. Firstly, an adaptive tone reservation assignment is performed by optimally choosing a group of subcarriers, whose channel gains are sufficiently high, to be the data subcarriers and the remaining subcarriers will be used as the reserved tones for reducing PAPR to the desired level. Secondly, an adaptive power adjustment for PAPR reduction technique is introduced for determining the allocated power of data subcarriers by using the water-filling approach with the joint PAPR and capacity constraints. By using the proposed joint algorithm, the PAPR threshold level is satisfied while the desired capacity could be achieved. From the results, the proposed algorithm achieves the better results comparing with a conventional partial transmit sequence (PTS) technique and the tone reservation (TR) technique in terms of PAPR, and probability of error performances, in which the side information is not required, in contrast with the other techniques.