Showing papers on "Channel allocation schemes published in 2012"

Throughput Optimization, Spectrum Allocation, and Access Control in Two-Tier Femtocell Networks

Abstract: The deployment of femtocells in a macrocell network is an economical and effective way to increase network capacity and coverage. Nevertheless, such deployment is challenging due to the presence of inter-tier and intra-tier interference, and the ad hoc operation of femtocells. Motivated by the flexible subchannel allocation capability of OFDMA, we investigate the effect of spectrum allocation in two-tier networks, where the macrocells employ closed access policy and the femtocells can operate in either open or closed access. By introducing a tractable model, we derive the success probability for each tier under different spectrum allocation and femtocell access policies. In particular, we consider joint subchannel allocation, in which the whole spectrum is shared by both tiers, as well as disjoint subchannel allocation, whereby disjoint sets of subchannels are assigned to both tiers. We formulate the throughput maximization problem subject to quality of service constraints in terms of success probabilities and per-tier minimum rates, and provide insights into the optimal spectrum allocation. Our results indicate that with closed access femtocells, the optimized joint and disjoint subchannel allocations provide the highest throughput among all schemes in sparse and dense femtocell networks, respectively. With open access femtocells, the optimized joint subchannel allocation provides the highest possible throughput for all femtocell densities.

Energy-Efficient Resource Allocation for Heterogeneous Cognitive Radio Networks with Femtocells

Abstract: Both cognitive radio and femtocell have been considered as promising techniques in wireless networks. However, most of previous works are focused on spectrum sharing and interference avoidance, and the energy efficiency aspect is largely ignored. In this paper, we study the energy efficiency aspect of spectrum sharing and power allocation in heterogeneous cognitive radio networks with femtocells. To fully exploit the cognitive capability, we consider a wireless network architecture in which both the macrocell and the femtocell have the cognitive capability. We formulate the energy-efficient resource allocation problem in heterogeneous cognitive radio networks with femtocells as a Stackelberg game. A gradient based iteration algorithm is proposed to obtain the Stackelberg equilibrium solution to the energy-efficient resource allocation problem. Simulation results are presented to demonstrate the Stackelberg equilibrium is obtained by the proposed iteration algorithm and energy efficiency can be improved significantly in the proposed scheme.

Fast Data Collection in Tree-Based Wireless Sensor Networks

Abstract: We investigate the following fundamental question-how fast can information be collected from a wireless sensor network organized as tree? To address this, we explore and evaluate a number of different techniques using realistic simulation models under the many-to-one communication paradigm known as convergecast. We first consider time scheduling on a single frequency channel with the aim of minimizing the number of time slots required (schedule length) to complete a convergecast. Next, we combine scheduling with transmission power control to mitigate the effects of interference, and show that while power control helps in reducing the schedule length under a single frequency, scheduling transmissions using multiple frequencies is more efficient. We give lower bounds on the schedule length when interference is completely eliminated, and propose algorithms that achieve these bounds. We also evaluate the performance of various channel assignment methods and find empirically that for moderate size networks of about 100 nodes, the use of multifrequency scheduling can suffice to eliminate most of the interference. Then, the data collection rate no longer remains limited by interference but by the topology of the routing tree. To this end, we construct degree-constrained spanning trees and capacitated minimal spanning trees, and show significant improvement in scheduling performance over different deployment densities. Lastly, we evaluate the impact of different interference and channel models on the schedule length.

Anti-Jamming Games in Multi-Channel Cognitive Radio Networks

Abstract: Crucial to the successful deployment of cognitive radio networks, security issues have begun to receive research interests recently. In this paper, we focus on defending against the jamming attack, one of the major threats to cognitive radio networks. Secondary users can exploit the flexible access to multiple channels as the means of anti-jamming defense. We first investigate the situation where a secondary user can access only one channel at a time and hop among different channels, and model it as an anti-jamming game. Analyzing the interaction between the secondary user and attackers, we derive a channel hopping defense strategy using the Markov decision process approach with the assumption of perfect knowledge, and then propose two learning schemes for secondary users to gain knowledge of adversaries to handle cases without perfect knowledge. In addition, we extend to the scenario where secondary users can access all available channels simultaneously, and redefine the anti-jamming game with randomized power allocation as the defense strategy. We derive the Nash equilibrium for this Colonel Blotto game which minimizes the worst-case damage. Finally, simulation results are presented to verify the performance.

A Dynamic Channel Assignment Scheme for Distributed Antenna Networks

Abstract: In this paper, we propose a dynamic channel assignment (DCA) scheme for distributed antenna networks (DANs). DANs, in which many antennas are distributed in each cell, significantly reduce the transmit power compared to conventional cellular networks (CNs). In DAN, a different group of channels should be assigned for each distributed antenna to avoid the interference. Since DAN can also reduce the interference power due to its low transmit power property, the same channel groups can be reused even within the same cell. Proposed DCA scheme dynamically assigns the channels based on the co-channel interference measurement. Computer simulation results demonstrate that the DAN using proposed DCA achieves higher spectrum efficiency than the conventional CN.

A Survey on Uplink Resource Allocation in OFDMA Wireless Networks

Abstract: OFDMA has been selected as the multiple access scheme for state-of-the-art wireless communication systems. Efficient resource allocation in OFDMA wireless networks is essential in order to meet the quality of service requirements of emerging services. In this paper, a survey of resource allocation and scheduling schemes in OFDMA wireless networks is presented. The focus is on the uplink direction. Resource allocation is surveyed in various scenarios: centralized and distributed, instantaneous and ergodic, optimal and suboptimal, single cell and multicell, cooperative and non-cooperative, in addition to different combinations of these variants. Directions for future research are outlined.

Low-Complexity Energy-Efficient Scheduling for Uplink OFDMA

Abstract: Energy-efficient wireless communication is very important for battery-constrained mobile devices. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget because of RF power requirements for reliable transmission over long distances. Our previous work in this area focused on optimizing energy efficiency by maximizing the instantaneous bits-per-Joule metric through iterative approaches, which resulted in significant energy savings for uplink cellular OFDMA transmissions. In this paper, we develop energy efficient schemes with significantly lower complexity when compared to iterative approaches, by considering time-averaged bits-per-Joule metrics. We consider an uplink OFDMA system where multiple users communicate to a central scheduler over frequency-selective channels with high energy efficiency. The scheduler allocates the system bandwidth among all users to optimize energy efficiency across the whole network. Using time-averaged metrics, we derive energy optimal techniques in "closed forms" for per-user link adaptation and resource scheduling across users. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions obtained through exhaustive search.

On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach

Abstract: The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.

Jump-Stay Rendezvous Algorithm for Cognitive Radio Networks

Abstract: Cognitive radio networks (CRNs) have emerged as advanced and promising paradigm to exploit the existing wireless spectrum opportunistically. It is crucial for users in CRNs to search for neighbors via rendezvous process and thereby establish the communication links to exchange the information necessary for spectrum management and channel contention, etc. This paper focuses on the design of algorithms for blind rendezvous, i.e., rendezvous without using any centralized controller and common control channel (CCC). We propose a jump-stay channel-hopping (CH) algorithm for blind rendezvous. The basic idea is to generate CH sequence in rounds and each round consists of a jump-pattern and a stay-pattern. Users “jump” on available channels in the jump-pattern while “stay” on a specific channel in the stay-pattern. We prove that two users can achieve rendezvous in one of four possible pattern combinations: jump-stay, stay-jump, jump-jump, and stay-stay. Compared with the existing CH algorithms, our algorithm has the overall best performance in various scenarios and is applicable to rendezvous of multiuser and multihop scenarios. We derive upper bounds on the maximum time-to-rendezvous (TTR) and the expected TTR of our algorithm for both 2-user and multiuser scenarios (shown in Table 1). Extensive simulations are conducted to evaluate the performance of our algorithm.

QoE-Driven Channel Allocation Schemes for Multimedia Transmission of Priority-Based Secondary Users over Cognitive Radio Networks

Abstract: With the fast growing of multimedia communication applications, cognitive radio networks have gained the popularity as they can provide high wireless bandwidth and support quality-driven wireless multimedia services. In multimedia applications such as video conferences over the cognitive radio, the Quality of Experience (QoE) that directly measures the satisfaction of the end users cannot be easily realized due to the limited spectrum resources. The opportunistic spectrum access cognitive radio (CR) is an efficient technology to address this issue. However, the unstable channels allocated to the multimedia secondary users (SUs) can be re-occupied by the primary users (PUs) at any time, which makes the CR difficult to meet the QoE requirements. Therefore, it is important to study how to allocate frequency or spectrum resources to SUs according to their QoE requirements. This paper proposes a novel QoE-driven channel allocation scheme for SUs and cognitive radio networks (CRN) base station (BS). The historical QoE data under different primary channels (PCs) are collected by the SUs and delivered to a Cognitive Radio Base Station (CRBS). The CRBS will allocate available channel resources to the SUs based on their QoE expectations and maintain a priority service queue. The modified ON/OFF models of PCs and service queue models of SUs are jointly investigated for this channel allocation scheme. The performance of multimedia transmission of images and H.264 videos under our CR channel allocation scheme is studied, the results show that the proposed channel allocation approach can significantly improve the QoE of the priority-based SUs over the cognitive radio networks.

Dynamic Resource Allocation for Heterogeneous Services in Cognitive Radio Networks With Imperfect Channel Sensing

Abstract: Resources in cognitive radio networks (CRNs) should dynamically be allocated according to the sensed radio environment Although some work has been done for dynamic resource allocation in CRNs, many works assume that the radio environment can perfectly be sensed However, in practice, it is difficult for the secondary network to have the perfect knowledge of a dynamic radio environment in CRNs In this paper, we study the dynamic resource allocation problem for heterogeneous services in CRNs with imperfect channel sensing We formulate the power and channel allocation problem as a mixed-integer programming problem under constraints The computational complexity is enormous to solve the problem To reduce the computational complexity, we tackle this problem in two steps First, we solve the optimal power allocation problem using the Lagrangian dual method under the assumption of known channel allocation Next, we solve the joint power and channel allocation problem using the discrete stochastic optimization method, which has low computational complexity and fast convergence to approximate to the optimal solution Another advantage of this method is that it can track the changing radio environment to dynamically allocate the resources Simulation results are presented to demonstrate the effectiveness of the proposed scheme

On the design of device-to-device autonomous discovery

Abstract: This paper proposes a synchronous device discovery solution for ad-hoc networks based on the observations that time synchronization, along with an FDM based channel resource allocation, can lead to gains in terms of energy consumption, discovery range, and the number of devices discovered. These attributes are important for the success of proximity-aware networking, where devices autonomously find peer-groups over human mobility scales. In this paper, we develop the PHY and MAC protocols to enable autonomous device discovery. Using both simulations and stochastic-geometry based analysis, we validate our design, and argue that there can be significant gains over a conventional Wi-Fi based solution.

Defeating Primary User Emulation Attacks Using Belief Propagation in Cognitive Radio Networks

Abstract: Cognitive radio (CR) is a promising technology for future wireless spectrum allocation to improve the usage of the licensed bands. However, CR wireless networks are susceptible to various attacks and cannot offer efficient security. Primary user emulation (PUE) is one of the most serious attacks for CR networks, which can significantly increase the spectrum access failure probability. In this paper, we propose a defense strategy against the PUE attack in CR networks using belief propagation, which avoids the deployment of additional sensor networks and expensive hardware in the networks used in the existing literatures. In our proposed approach, each secondary user calculates the local function and the compatibility function, computes the messages, exchanges messages with the neighboring users, and calculates the beliefs until convergence. Then, the PUE attacker will be detected, and all the secondary users in the network will be notified in a broadcast way about the characteristics of the attacker's signal. Therefore, all SUs can avoid the PUE attacker's primary emulation signal in the future. Simulation results show that our proposed approach converges quickly, and is effective to detect the PUE attacker.

Spectrum sharing and resource allocation for energy-efficient heterogeneous cognitive radio networks with femtocells

Abstract: In heterogeneous wireless networks with femtocells, the issue of interference between femtocells and macrocells should be carefully considered. Using cognitive radio for interference management is a promising technique in heterogeneous wireless networks with femtocells. In this paper, we study the energy efficiency aspect of spectrum sharing and resource allocation in heterogeneous wireless networks with femtocells and cognitive radios. We use the price of interference to model the interference between femtocells and macrocells. We formulate the problem of interference management and power allocation as a Stackelberg game. In addition, an iteration algorithm based on price updating is proposed to obtain the Stackelberg equilibrium solution to the resource allocation problem for energy efficiency. Simulation results are presented to show that the proposed scheme can improve energy efficiency significantly in heterogeneous wireless networks with femtocells and cognitive radios.

An optimal energy allocation algorithm for energy harvesting wireless sensor networks

Abstract: With the use of energy harvesting technologies, the lifetime of a wireless sensor network (WSN) can be prolonged significantly. Unlike a traditional WSN powered by non-rechargeable batteries, the energy management policy of an energy harvesting WSN needs to take into account the energy replenishment process. In this paper, we study the energy allocation for sensing and transmission in an energy harvesting sensor node with a rechargeable battery and a finite data buffer. The sensor node aims to maximize the total throughput in a finite horizon subject to time-varying energy harvesting rate, energy availability in the battery, and channel fading. We formulate the energy allocation problem as a sequential decision problem and propose an optimal energy allocation (OEA) algorithm using dynamic programming. We conduct simulations to compare the performance between our proposed OEA algorithm and the channel-aware energy allocation (CAEA) algorithm from [1]. Simulation results show that the OEA algorithm achieves a higher throughput than the CAEA algorithm under different settings.

Coexistence of lte operated in unlicesnsed band

Abstract: A cellular access node collects information about at least interference in a plurality of channels in unlicensed spectrum, and uses that collected information to update an allocation of the channels among at least two different access points APs. In one embodiment the information is collected from measurement reports received from each AP which indicates whether the various respective channels are available or reserved. Additional measurement reports may be collected from user equipments operating under the APs. In various embodiments the information can include channel recommendations, estimated capacity for the channels, and/or a traffic model for the channels. With this collected information the cellular access node can balance traffic among the APs by its channel allocation decisions. The non-limiting examples assume a radio environment where a LTE cellular access node operates a primary component carrier in licensed spectrum and the cooperating APs operate secondary component carriers in unlicensed spectrum.

Using Partially Overlapping Channels to Improve Throughput in Wireless Mesh Networks

Abstract: Wireless mesh networks have attracted great interest in the research community recently. Much effort has been devoted to maximizing the network performance using limited channel resources in a multichannel multiradio wireless mesh network. It is believed that the limited spectrum resource can be fully exploited by utilizing partially overlapping channels in addition to nonoverlapping channels in 802.11b/g networks. However, there are only few studies of channel assignment algorithms for partially overlapping channels. In this paper, we first formulate the optimal channel assignment problem with the goal of maximizing the overall network throughput or maximizing the throughput of a multicast application. For both cases, we present a greedy algorithm for partially overlapping channel assignment, and then propose a novel genetic algorithm, which has the potential to obtain better solutions. Through evaluation, we demonstrate that the overall network throughput can be dramatically improved by properly utilizing the partially overlapping channels. The genetic algorithm outperforms the greedy algorithm in mitigating the network interference, and therefore leads to higher network throughput. In addition, the multicast throughput can also be dramatically improved by using our algorithms compared to previous work.

Cluster-Based Control Channel Allocation in Opportunistic Cognitive Radio Networks

Abstract: Cognitive radio networks (CRNs) involve extensive exchange of control messages, which are used to coordinate critical network functions such as distributed spectrum sensing, medium access, and routing, to name a few. Typically, control messages are broadcasted on a preassigned common control channel, which can be realized as a separate frequency band in multichannel systems, a given time slot in TDMA systems, or a frequency hopping sequence (or CDMA code) in spread spectrum systems. However, a static control channel allocation is contrary to the opportunistic access paradigm. In this paper, we address the problem of dynamically assigning the control channel in CRNs based on time- and space-varying spectrum opportunities. We propose a cluster-based architecture that allocates different channels for control at various clusters in the network. The clustering problem is formulated as a bipartite graph problem, for which we develop a class of algorithms that provide different tradeoffs between two conflicting factors: number of common channels in a cluster and the cluster size. Clusters are guaranteed to have a desirable number of common channels for control, which facilitates for graceful channel migration when primary radio (PR) activity is detected, without the need for frequent reclustering. We perform extensive simulations that verify the agility of our algorithms in adapting to spatial-temporal variations in spectrum availability.

Optimal Channel and Relay Assignment in OFDM-Based Multi-Relay Multi-Pair Two-Way Communication Networks

Abstract: Efficient utilization of radio resources in wireless networks is crucial and has been investigated extensively. This letter considers a wireless relay network where multiple user pairs conduct bidirectional communications via multiple relays based on orthogonal frequency-division multiplexing (OFDM) transmission. The joint optimization of channel and relay assignment, including subcarrier pairing, subcarrier allocation as well as relay selection, for total throughput maximization is formulated as a combinatorial optimization problem. Using a graph theoretical approach, we solve the problem optimally in polynomial time by transforming it into a maximum weighted bipartite matching (MWBM) problem. Simulation studies are carried out to evaluate the network total throughput versus transmit power per node and the number of relay nodes.

Shared-path protection in OFDM-based optical networks with elastic bandwidth allocation

Abstract: Compared with backup sharing in WDM networks, it is more complex and challenging to share backup resources in OFDM-based optical networks with elastic bandwidth allocation. We propose and evaluate conservative and agressive backup sharing policies.

On Hybrid ARQ and Quantized CSI Feedback Schemes in Quasi-Static Fading Channels

Abstract: Recently, substantial attention has been paid to increase the achievable rates of wireless networks using different kinds of limited channel quality information feedback. Hybrid automatic repeat request (ARQ) and quantized channel state information (CSI) feedback are two well-known approaches applied by experts to provide the limited channel quality information at the transmitter. Considering quasi-static fading channels, this paper aims to provide some comparisons between the performance of these methods from different points of view. The paper first investigates the power- and outage-limited performance of hybrid ARQ and quantized CSI schemes under short- and long-term power constraints. Then, 1) the feedback signaling load, 2) robustness and 3) the complexity of these schemes are compared under short-term transmission power constraint. Both INcremental Redundancy (INR) and Repetition Time Diversity (RTD) approaches are considered for hybrid ARQ feedback. Finally, approximate low-complexity solutions are presented for power allocation in the INR ARQ-based scheme under long-term transmission power constraint. Analytical and numerical results demonstrate the equivalency or the superiority of these approaches in different circumstances.

Adaptive time slotted channel hopping for wireless sensor networks

Abstract: The performance of wireless sensor networks (WSN) is prone to adverse influences from a number of factors such as the interference from co-located wireless systems utilising the same spectral space. Channel hopping technique was proposed to mitigate the problem via periodic change of the operating frequency, and has been adopted in the form of time slotted channel hopping (TSCH) by IEEE 802.15.4e standard. This paper proposes adaptive slotted channel hopping (A-TSCH), an enhanced version of the TSCH aided by blacklisting technique. Complete design and implementation specifics are provided; and the results of experiments are analysed to show its advantages over existing TSCH. The main finding of this work is that A-TSCH can significantly improve the reliability of channel hopping scheme and thus provide better protection from interference for wireless sensor networks.

A Study of Deterministic Pilot Allocation for Sparse Channel Estimation in OFDM Systems

Abstract: In this letter, we investigate the deterministic pilot allocation for sparse channel estimation in OFDM systems. Based on the rule of minimizing the coherence of the DFT submatrix, we derive that the pilot design according to the cyclic different set (CDS) is optimal. However, the CDS only exists for some specific number of OFDM subcarriers. For those cases where the CDS is unavailable, we propose a scheme using discrete stochastic approximation to obtain a near-optimal pilot pattern. Simulation results demonstrate that our scheme is much faster convergent and more efficient than the exhaustive search; and it has been shown that substantial improvement for channel estimation can be achieved.

Radio communication method and radio communication device

Abstract: PROBLEM TO BE SOLVED: To provide a radio communication method and a radio communication device, capable of improving a throughput in consideration of QoS, without need of the detection of a travelling speed of each terminal, in a radio communication method with a plurality of terminals based on an adaptive modulation system using a space division multiple access scheme.SOLUTION: A radio communication device 100 includes: a data rate acquisition unit 190 for acquiring a downlink data rate in each terminal; based on uplink signal quality in each terminal, a data rate estimation unit 140 for estimating the downlink data rate in each terminal; a data rate difference calculation unit 150 for obtaining a difference between the data rate estimated in the data rate estimation unit and the data rate acquired in the data rate acquisition unit, on the basis of each terminal; and based on the data rate difference obtained in the data rate calculation unit, a channel allocation control unit 180 for controlling channel allocation to each terminal.

A Novel Distributed Asynchronous Multichannel MAC Scheme for Large-Scale Vehicular Ad Hoc Networks

Abstract: This paper proposes a novel distributed asynchronous multichannel medium access control (MAC) scheme for large-scale vehicular ad hoc networks (VANETs), i.e., asynchronous multichannel medium access control with a distributed time-division multiple-access mechanism (AMCMAC-D). The proposed scheme supports simultaneous transmissions on different service channels while allowing rendezvous and broadcast of emergency messages on the control channel. The scheme is distributed, because it handles access to the shared control channel for different access categories without relying on the beacon frames from roadside units. This condition eliminates the overhead that is associated with channel allocation, making the proposed scheme suitable for large-scale networks in terms of the number of active nodes. Service differentiation in the proposed scheme is enhanced by allocating different numbers of time slots for different access categories. We compare the performance of the proposed scheme with the IEEE 1609.4 standard and the asynchronous multichannel Coordination Protocol (AMCP) in terms of throughput, packet delivery rate, collision rate, utilization of service channels, service differentiation, and the penetration rate of noncollided emergency messages. The results show that AMCMAC-D outperforms the IEEE 1609.4 standard and AMCP in terms of system throughput by increasing the utilization of the control channel and service channels. The proposed scheme also demonstrates better performance in terms of packet delivery rate, collision rate on a service channel, load balancing, and service differentiation. Finally, AMCMAC-D mitigates the multichannel hidden terminal and missing receiver problems, which occur in asynchronous multichannel MAC schemes.

Joint Base-Station Association, Channel Assignment, Beamforming and Power Control in Heterogeneous Networks

Abstract: Heterogeneous cellular networks (HetNets), where low-power base-stations are overlaid with conventional macro base-stations, is a promising technique to improve coverage and capacity of the macro-only networks. To realize the potential benefits of HetNets, it is crucial to jointly optimize the user association, channel assignment, beamforming and power control to ensure that the inter- and intra-cell interference will not overwhelm the cell-splitting gains. This paper presents an iterative algorithm to solve the joint optimization problem with an objective of maximizing the network sum rate and simultaneously guaranteeing the individual user quality-of-service. The proposed algorithm is built on the so-called convex-concave procedure, and the feasibility issue is handled by L1-norm heuristic. Numerical results demonstrate the large gains over currently used methods for cellular networks.

Side Channel: Bits over Interference

Abstract: Interference is a critical issue in wireless communications. In a typical multiple-user environment, different users may severely interfere with each other. Coordination among users therefore is an indispensable part for interference management in wireless networks. It is known that coordination among multiple nodes is a costly operation taking a significant amount of valuable communication resource. In this paper, we have an interesting observation that by generating intended patterns, some simultaneous transmissions, i.e., "interference,” can be successfully decoded without degrading the effective throughput in original transmission. As such, an extra and "free” coordination channel can be built. Based on this idea, we propose a DC-MAC to leverage this "free” channel for efficient medium access in a multiple-user wireless network. We theoretically analyze the capacity of this channel under different environments with various modulation schemes. USRP2-based implementation experiments show that compared with the widely adopted CSMA, DC-MAC can improve the channel utilization efficiency by up to 250 percent.

HERA: An Optimal Relay Assignment Scheme for Cooperative Networks

Abstract: Exploiting the nature of broadcast and the relaying capability of wireless devices, cooperative communication is becoming a promising technology to increase the channel capacity in wireless networks. In cooperative communication, the scheme for assigning relay nodes to users plays a critical role in the resulting channel capacity. A significant challenge is how to make the scheme robust to selfish and cheating behavior of users while guaranteeing the social optimal system capacity. In this paper, we design an integrated optimal marriage scheme called HERA for cooperative networks. To avoid system performance degradation due to the selfish relay selections by the source nodes, we propose a payment mechanism for charging the source nodes to induce them to converge to the optimal assignment. To prevent relay nodes from manipulating the marriage by reporting transmission power untruthfully, we propose a payment mechanism to pay them for providing relaying service. We also show that HERA is budget-balanced, meaning that the payment collected from source nodes is no smaller than the payment paid to relay nodes.

Truthful spectrum auction design for secondary networks

Abstract: Opportunistic wireless channel access by non-licensed users has emerged as a promising solution for addressing the bandwidth scarcity challenge. Auctions represent a natural mechanism for allocating the spectrum, generating an economic incentive for the licensed user to relinquish channels. A severe limitation of existing spectrum auction designs lies in the over-simplifying assumption that every non-licensed user is a single-node or single-link secondary user. While such an assumption makes the auction design easier, it does not capture practical scenarios where users have multihop routing demands. For the first time in the literature, we propose to model non-licensed users as secondary networks (SNs), each of which comprises of a multihop network with end-to-end routing demands. We aim to design truthful auctions for allocating channels to SNs in a coordinated fashion that maximizes social welfare of the system. We use simple examples to show that such auctions among SNs differ drastically from simple auctions among single-hop users, and previous solutions suffer severely from local, per-hop decision making. We first design a simple, heuristic auction that takes inter-SN interference into consideration, and is truthful. We then design a randomized auction based on primal-dual linear optimization, with a proven performance guarantee for approaching optimal social welfare. A key technique in our solution is to decompose a linear program (LP) solution for channel assignment into a set of integer program (IP) solutions, then applying a pair of tailored primal and dual LPs for computing probabilities of choosing each IP solution. We prove the truthfulness and performance bound of our solution, and verify its effectiveness through simulation studies.

Joint Power and Bandwidth Allocation Algorithm with QoS Support in Heterogeneous Wireless Networks

Abstract: Heterogeneous wireless networks give rise to a multi-radio access environment which becomes crucial for load balancing to avoid network congestion and providing high quality services to maximize radio resource utilization. To this end, a joint power and bandwidth allocation with QoS support algorithm is proposed using convex optimization method in this letter. The algorithm achieves the goal of the total system capacity maximization, while efficiently satisfying the minimum rate constraint of delay-constraint service traffic and proportional fairness of best-effort service traffic. The simulation results show that the proposed algorithm significantly outperforms the existing scheme in QoS guarantee.