Joint Spectrum Allocation Research Articles

Pre-reservation based spectrum allocation for cognitive radio network

Studies on the current usage of the radio spectrum by several agencies have already revealed that a large fraction of the radio spectrum is inadequately utilized. This basic finding has led to numerous research initiatives. Cognitive radio technology is one of the key candidate technologies to solve the problems of spectrum scarcity and low spectrum utilization. However, random behavior of the primary user (PU) appears to be an enormous challenge. In this paper, a Pre-reservation based spectrum allocation method for cognitive radio network is proposed to apply a PU behavior aware joint spectrum band (SB) selection and allocation scheme. In the first step, the SB is observed in terms of PU usage statistics whereas in the second phase, a network operator (NO) using a spectrum allocation scheme is employed to allocate SBs among secondary users (SUs). We also introduce the concept of reservation and exchange functionality under the priority serving strategy in a time-varying framing process. Simulation results show that the proposed scheme outperforms existing schemes in terms of the spectrum utilization and network revenue. In addition, it helps NO to manage the spectrum on a planned basis with a systematical spectrum reservation management where the NO has the status of time slots. Moreover, SUs have an opportunity to reserve or instantly request a SB that maximizes the SUs satisfaction in terms of quality of experience.

Scalable Spectrum Allocation and User Association in Networks With Many Small Cells

A scalable framework is developed to allocate radio resources across a large number of densely deployed small cells with given traffic statistics on a slow timescale. Joint user association and spectrum allocation is first formulated as a convex optimization problem by dividing the spectrum among all possible transmission patterns of active access points (APs). To improve scalability with the number of APs, the problem is reformulated using local patterns of interfering APs. To maintain global consistency among local patterns, inter-cluster interaction is characterized as hyper-edges in a hyper-graph with nodes corresponding to subcarriers allocated to APs. A scalable solution is obtained by iteratively solving a convex optimization problem for bandwidth allocation with reduced complexity and followed by a global spectrum allocation using hyper-graph coloring. Numerical results demonstrate the proposed solution for a network with 100 APs and several hundred user equipment. For a given quality of service, the proposed scheme can often increase the network capacity severalfold compared with assigning each user to the strongest AP with full-spectrum reuse.

An efficient joint spectrum and power allocation in cognitive radio networks using a modified firefly algorithm

In this paper, the applicability and efficiency of the new meta-heuristic algorithm called firefly algorithm to solve the joint power control and channel allocation problem in cognitive radio networks is studied. A modified version of the firefly algorithm (MFA) using the new attractiveness factor is proposed to solve the problem. Theoretical analysis is presented to prove effectiveness and the existence of Nash equilibrium of the proposed strategy. Simulation results of this study show that the proposed power control based on modified firefly algorithm cannot only able to find the optimal transmit power that maximises each secondary's own utility but also improves the fairness among secondary users and satisfies the outage probability constraints. Our results show that the proposed method outperforms previous approaches (including the standard firefly algorithm) in terms of convergence speed.

An efficient joint spectrum and power allocation in cognitive radio networks using a modified firefly algorithm

An efficient joint spectrum and power allocation in cognitive radio networks using a modified firefly algorithm

Auction-based resource allocation for cooperative cognitive radio networks

Cooperative cognitive radio network (CCRN) is a promising paradigm to increase spectrum utilization and exploit spatial diversity. The allocation of two coupled resources, i.e. spectrum and secondary relay nodes, plays a fundamental role in the performance of CCRNs. However, previous studies either lack of incentives for both primary users (PUs) and relay nodes to participate in or consider spectrum auction and relay auction separately. In this paper, we consider a static cooperative cognitive radio network scenario with several PUs and multiple secondary user coteries, each of which consists of a set of secondary users who are interested in sharing the same secondary relay node. We model the problem of joint spectrum allocation and relay allocation as a hierarchical auction and propose two auction schemes, i.e. TERA and UERA. TERA is the first Truthful auction mechanism for Efficient Resource Allocation in CCRNs which satisfies critical economic properties. UERA is an approximate truthful scheme which adopts a uniform price for fairness in the same secondary user coteries. Furthermore, we theoretically prove TERA and UERA can achieve near-optimal revenue. Finally, extensive simulation results show that TERA and UERA are efficient and able to improve the utility of PUs and relay nodes significantly.

Joint User Association and Spectrum Allocation for Small Cell Networks With Wireless Backhauls

Heterogenous networks and massive MIMO can significantly enhance spectral and energy efficiencies of wireless networks and have recently attracted lots of attention. In this letter, we investigate joint user association and spectrum allocation to further improve spectral efficiency for massive MIMO enabled heterogeneous networks with full-duplex wireless backhauls. The optimization problem is formulated as a mixed-integer nonlinear programming problem, and therefore, is nonconvex and combinational. To solve the problem efficiently, the original optimization problem is divided into two subproblems that can be solved with low-computational-complexity methods. The simulation results confirm our theoretical analysis and demonstrate the performance improvement of the proposed algorithm.

Joint Spectrum and IT Resource Allocation for Efficient VNF Service Chaining in Inter-Datacenter Elastic Optical Networks

We study how to allocate spectrum and IT resources jointly for realizing efficient virtual network function (VNF) service chaining in inter-datacenter elastic optical networks. We first formulate an integer linear programming model to solve the problem exactly, and then a longest common subsequence-based heuristic is proposed. The simulation results indicate that the proposed algorithms can reuse the deployed VNFs efficiently and arrange the spectrum utilization in a much more load-balanced manner.

Joint Spectrum and Power Allocation for D2D Communications Underlaying Cellular Networks

This paper addresses the joint spectrum sharing and power allocation problem for device-to-device (D2D) communications underlaying a cellular network (CN). In the context of orthogonal frequency-division multiple-access systems, with the uplink resources shared with D2D links, both centralized and decentralized methods are proposed. Assuming global channel state information (CSI), the resource allocation problem is first formulated as a nonconvex optimization problem, which is solved using convex approximation techniques. We prove that the approximation method converges to a suboptimal solution and is often very close to the global optimal solution. On the other hand, by exploiting the decentralized network structure with only local CSI at each node, the Stackelberg game model is then adopted to devise a distributed resource allocation scheme. In this game-theoretic model, the base station (BS), which is modeled as the leader, coordinates the interference from the D2D transmission to the cellular users (CUs) by pricing the interference. Subsequently, the D2D pairs, as followers, compete for the spectrum in a noncooperative fashion. Sufficient conditions for the existence of the Nash equilibrium (NE) and the uniqueness of the solution are presented, and an iterative algorithm is proposed to solve the problem. In addition, the signaling overhead is compared between the centralized and decentralized schemes. Finally, numerical results are presented to verify the proposed schemes. It is shown that the distributed scheme is effective for the resource allocation and could protect the CUs with limited signaling overhead.

Iterative Energy-Efficient Stable Matching Approach for Context-Aware Resource Allocation in D2D Communications

Energy efficiency (EE) is critical to fully achieve the huge potentials of device-to-device (D2D) communications with limited battery capacity. In this paper, we consider the two-stage EE optimization problem, which consists of a joint spectrum and power allocation problem in the first stage, and a context-aware D2D peer selection problem in the second stage. We provide a general tractable framework for solving the combinatorial problem, which is NP-hard due to the binary and continuous optimization variables. In each stage, user equipments (UEs) from two finite and disjoint sets are matched in a two-sided stable way based on the mutual preferences. First, the preferences of UEs are defined as the maximum achievable EE. An iterative power allocation algorithm is proposed to optimize EE under a specific match, which is developed by exploiting nonlinear fractional programming and Lagrange dual decomposition. Second, we propose an iterative matching algorithm, which first produces a stable match based on the fixed preferences, and then dynamically updates the preferences according to the latest matching results in each iteration. Finally, the properties of the proposed algorithm, including stability, optimality, complexity, and scalability, are analyzed in detail. Numerical results validate the efficiency and superiority of the proposed algorithm under various simulation scenarios.

Rate Maximization Through Structured Spectrum Allocation and User Association in Heterogeneous Cellular Networks

We study joint spectrum allocation and user association in heterogeneous cellular networks with multiple tiers of base stations. A stochastic geometric approach is applied as the basis to derive the average downlink user data rate in a closed-form expression. Then, the expression is employed as the objective function in jointly optimizing spectrum allocation and user association, which is of a non-convex programming in nature. A computationally efficient structured spectrum allocation and user association (SSAUA) approach is proposed, solving the problem optimally and asymptotically optimally in two regions divided by a parameter specific threshold. A surcharge pricing scheme (SPS) is also presented, such that the designed association bias values can be achieved in Nash equilibrium. Simulations and numerical studies are conducted to validate the accuracy and efficiency of the proposed SSAUA approach and SPS.

Joint Spectrum and Power Allocation for Multi-Node Cooperative Wireless Systems

Energy efficiency is a growing concern for wireless networks, not only due to the emerging traffic demand from smart devices, but also because of the dependence on the traditional unsustainable energy and the overall environmental concerns. The urgent call for reducing power consumption while meeting system requirements has motivated increasing research efforts on green radio. In this paper, we investigate a new joint spectrum and power allocation scheme for a cooperative downlink multi-user system using the frequency division multiple access scheme, in which arbitrary $M$ base stations (BSs) coordinately allocate their resources to each user equipment (UE). With the assumption that multi-BS UE (user being served by multi-BS) would require the same amount of spectrum from these BSs, we conclude that when the number of multi-BS UEs is limited by $M-1$ , the resource allocation scheme can always guarantee the minimum overall transmit power consumption while meeting the throughput requirement of each UE and also each BS’s power constraint. Then, to decide the clusters of multi-BS UEs and the clusters of individual-BS UEs (users being served by individual BSs), we propose a UE-BS association scheme and a complexity reduction scheme. Finally, a novel joint spectrum and power allocation algorithm is proposed to minimize the total power consumption. Simulation results are presented to verify the optimality of the derived schemes.

Joint Routing and Spectrum Allocation for Multi-hop Inter-Vehicle Communication in Cognitive Radio Networks

In multi-hop inter-vehicle communications (MHIVC) for cognitive radio (CR), high mobility of vehicles causes the situation change of the primary user (PU) near the secondary user (SU) and changes a link distance in a short time. In this paper, in order to overcome these problems, we propose a joint routing and spectrum allocation utilizing the PU information (e.g., position, channel, and transmit power) and vehicle mobility information (e.g., position, direction, and speed) to predict the end-to-end delay time for sending required packets. By using PU information, we predict a period of SU’s available frequency according to SU’s mobility. By using SU’s mobility information, we predict the available transmission data rate of each frequency. The proposed joint routing and spectrum allocation is more likely to establish minimum delay time multi-hop paths for VANET. By using computer simulations, we confirm the effectiveness of the proposed method in terms of end-to-end delay time.

Distributed resource allocation in cognitive and cooperative ad hoc networks through joint routing, relay selection and spectrum allocation

Cooperative relaying and dynamic-spectrum-access/cognitive techniques are promising solutions to increase the capacity and reliability of wireless links by exploiting the spatial and frequency diversity of the wireless channel. Yet, the combined use of cooperative relaying and dynamic spectrum access in multi-hop networks with decentralized control is far from being well understood.We study the problem of network throughput maximization in cognitive and cooperative ad hoc networks through joint optimization of routing, relay assignment and spectrum allocation. We derive a decentralized algorithm that solves the power and spectrum allocation problem for two common cooperative transmission schemes, decode-and-forward (DF) and amplify-and-forward (AF), based on convex optimization and arithmetic–geometric mean approximation techniques. We then propose and design a practical medium access control protocol in which the probability of accessing the channel for a given node depends on a local utility function determined as the solution of the joint routing, relay selection, and dynamic spectrum allocation problem. Therefore, the algorithm aims at maximizing the network throughput through local control actions and with localized information only.Through discrete-event network simulations, we finally demonstrate that the protocol provides significant throughput gains with respect to baseline solutions.

Joint Spectrum and Power Allocation for Green D2D Communication with Physical Layer Security Consideration

In this paper, we consider cooperative D2D communications in cellular networks. More precisely, a cellular user leases part of its spectrum to facilitate the D2D communication with a goal of improving the energy efficiency of a D2D pair. However the D2D pair is untrusted to the cellular user, such resource sharing may result in the information of this cellular user unsecured. In order to motivate the cellular user’s generosity, this D2D pair needs to help the cellular user maintain a target secrecy rate. To address this issue, we formulate a joint spectrum and power allocation problem to maximize the energy efficiency of the D2D communication while guaranteeing the physical layer security of the cellular user. Then, a theorem is proved to indicate the best resource allocation strategy, and accordingly, an algorithm is proposed to find the best solution to this resource allocation problem. Numerical results are finally presented to verify the validity and effectiveness of the proposed algorithm.

Pricing-Based Interference Coordination for D2D Communications in Cellular Networks

A pricing-based joint spectrum and power allocation framework is proposed for decentralized interference coordination among device-to-device (D2D) communications and cellular users (CUs), with the quality-of-service guarantee. The interlayer interference from D2D pairs to CUs is controlled by the base station through setting a price for each D2D channel usage. The intralayer interference among D2D pairs is mitigated distributively using a game-theoretic approach, where the D2D pairs compete for the spectrum until a Nash equilibrium is achieved. The effectiveness of the proposed strategy, including a practical scheme with limited signaling overhead, is demonstrated through comparing with a centralized scheme.

Optimizing User Association and Spectrum Allocation in HetNets: A Utility Perspective

The joint user association and spectrum allocation problem is studied for multi-tier heterogeneous networks (HetNets) in both downlink and uplink in the interference-limited regime. Users are associated with base-stations (BSs) based on the biased downlink received power. Spectrum is either shared or orthogonally partitioned among the tiers. This paper models the placement of BSs in different tiers as spatial point processes and adopts stochastic geometry to derive the theoretical mean proportionally fair utility of the network based on the coverage rate. By formulating and solving the network utility maximization problem, the optimal user association bias factors and spectrum partition ratios are analytically obtained for the multi-tier network. The resulting analysis reveals that the downlink and uplink user associations do not have to be symmetric. For uplink under spectrum sharing, if all tiers have the same target signal-to-interference ratio (SIR), distance-based user association is shown to be optimal under a variety of path loss and power control settings. For both downlink and uplink, under orthogonal spectrum partition, it is shown that the optimal proportion of spectrum allocated to each tier should match the proportion of users associated with that tier. Simulations validate the analytical results. Under typical system parameters, simulation results suggest that spectrum partition performs better for downlink in terms of utility, while spectrum sharing performs better for uplink with power control.

Joint Spectrum and Power Auction With Multiauctioneer and Multibidder in Coded Cooperative Cognitive Radio Networks

In the existing cooperative cognitive radio (CR), qualities of service (e.g., rate or outage probability) of primary users can be improved by cooperative transmission from sec- ondary users. However, as owners of the spectrum, primary users' traffic demands are relatively easy to satisfy. The rationale is that they would be more interested in the benefits of other formats (e.g., revenue), rather than the enhanced rate. In this paper, we propose a new cooperative CR framework, where primary users assist in the transmissions of secondary users. In exchange for this concession, primary users receive payments from secondary users for the spectrum and cooperative transmit power being used in cooperation. An auction-theoretic model with multiple auctioneers, multiple bidders, and multiple commodities is de- veloped for a joint spectrum and cooperative power allocation. Since the spectrum and power are two heterogeneous but corre- lated commodities, their properties are specifically considered in auction strategy design. Finally, we mathematically prove the con- vergence of the proposed auction game, and show with numerical results, that the proposed auction is beneficial to both primary and secondary users.

Joint subcarrier, code, and power allocation for parallel multi-radio access in heterogeneous wireless networks

In the heterogeneous wireless networks, it has been proved that the joint spectrum and power allocation can achieve network diversity gains for parallel multi-radio access in theory. This article aims to develop an effective and practical algorithm of joint subcarrier, code, and power allocation for parallel multi-radio access of the downlink in heterogeneous wireless networks (e.g., CDMA and OFDMA). Firstly, we propose a unified framework to formulate the subcarrier, code, and power allocation as an optimization problem. Secondly, we propose a resource element (subcarrier and code) scheme based on the threshold type. Simulation results show that the proposed scheme outperforms the existing algorithm for considered wireless scenarios.

Joint Spectrum and Power Allocation for Femtocell Based on Graph and Game Theory

In order to mitigate the downlink interference in two-tier femtocell networks, a joint spectrum and power allocation algorithm based on graph and game theory is proposed in this paper. On the premise of ensuring the QoS (Quality of Service) of MUEs (microcell user equipments), we first adopt graph-based clustering algorithm to assign subbands to femtocells. Then, for femtocells of each cluster, their transmitting power is redistributed based on the non-cooperative game theory to further reduce the interference among them. Simulation results show that this algorithm can further improves the performance of the entire system compared with pure clustering strategy and ensures the QoS of MUEs at the same time.

Synergy routing and dynamic spectrum allocation in multi‐hop cognitive radio networks

To maximise spectrum efficiency and channel capacity, both unused (white) and underused (grey) spectral regions need to be exploited. The authors propose a distributed and localised algorithm for joint opportunistic routing and spectrum allocation for multi-hop cognitive radio networks, and design a synergy routing, a utility-based routing scheme that achieves synergistic cognitive radio benefits of overlay and underlay techniques and simultaneously maximises spectrum efficiency. The synergy routing opportunistically calculates the next hop according to the spectrum dynamics and residual energy of candidate relays and harvests the benefits from the cooperation of underlay and overlay spectrum. Simulation results indicate that our synergy prototype improves delay and throughput performance, while maintaining the autonomy and heterogeneity of individual underlay and overlay networks.