Showing papers on "Channel allocation schemes published in 2010"

Energy-efficient link adaptation in frequency-selective channels

Abstract: Energy efficiency is becoming increasingly important for small form factor mobile devices, as battery technology has not kept up with the growing requirements stemming from ubiquitous multimedia applications. This paper addresses link adaptive transmission for maximizing energy efficiency, as measured by the "throughput per Joule" metric. In contrast to the existing water-filling power allocation schemes that maximize throughput subject to a fixed overall transmit power constraint, our scheme maximizes energy efficiency by adapting both overall transmit power and its allocation, according to the channel states and the circuit power consumed. We demonstrate the existence of a unique globally optimal link adaptation solution and develop iterative algorithms to obtain it. We further consider the special case of flat-fading channels to develop an upper bound on energy efficiency and to characterize its variation with bandwidth, channel gain and circuit power. Our results for OFDM systems demonstrate improved energy savings with energy optimal link adaptation as well as illustrate the fundamental tradeoff between energy-efficient and spectrum-efficient transmission.

Learning Multiuser Channel Allocations in Cognitive Radio Networks: A Combinatorial Multi-Armed Bandit Formulation

Abstract: We consider the following fundamental problem in the context of channelized dynamic spectrum access. There are $M$ secondary users and $N \ge M$ orthogonal channels. Each secondary user requires a single channel for operation that does not conflict with the channels assigned to the other users. Due to geographic dispersion, each secondary user can potentially see different primary user occupancy behavior on each channel. Time is divided into discrete decision rounds. The throughput obtainable from spectrum opportunities on each user-channel combination over a decision period is modeled as an arbitrarily-distributed non-negative random variable with bounded support but unknown mean, i.i.d. over time. The objective is to search for an allocation of channels for all users that maximizes the expected sum throughput. We formulate this problem as a combinatorial multi-armed bandit (MAB), in which each arm corresponds to a matching of the users to channels. Unlike most prior work on multi-armed bandits, this combinatorial formulation results in dependent arms. Moreover, the number of arms grows super-exponentially as the permutation $P(N,M)$. We present a novel matching-learning algorithm with polynomial storage and polynomial computation per decision period for this problem, and prove that it results in a regret (the gap between the expected sum-throughput obtained by a genie-aided perfect allocation and that obtained by this algorithm) that is uniformly upper-bounded for all time $n$ by a function that grows as $O(M^4 N log n)$, i.e. polynomial in the number of unknown parameters and logarithmic in time. We also discuss how our results provide a non-trivial generalization of known theoretical results on multi-armed bandits.

Channel assignment schemes for infrastructure-based 802.11 WLANs: A survey

Abstract: Efficient channel assignment is crucial for successful deployment and operation of IEEE 802.11-based WLANs. In this article we present a survey on the state of the art channel assignment schemes in IEEE 802.11-based WLANs. After detailing out all the schemes, we provide a qualitative comparison among different schemes in terms of algorithm execution behaviors, complexity, and scalability. We then conclude the survey with several research issues open for further investigation.

Interference management for 4G cellular standards [WIMAX/LTE UPDATE]

Abstract: 4G cellular standards are targeting aggressive spectrum reuse (frequency reuse 1) to achieve high system capacity and simplify radio network planning. The increase in system capacity comes at the expense of SINR degradation due to increased intercell interference, which severely impacts cell-edge user capacity and overall system throughput. Advanced interference management schemes are critical for achieving the required cell edge spectral efficiency targets and to provide ubiquity of user experience throughout the network. In this article we compare interference management solutions across the two main 4G standards: IEEE 802.16m (WiMAX) and 3GPP-LTE. Specifically, we address radio resource management schemes for interference mitigation, which include power control and adaptive fractional frequency reuse. Additional topics, such as interference management for multitier cellular deployments, heterogeneous architectures, and smart antenna schemes will be addressed in follow-up papers.

Power Control and Channel Allocation in Cognitive Radio Networks with Primary Users' Cooperation

Abstract: We consider a point-to-multipoint cognitive radio network that shares a set of channels with a primary network. Within the cognitive radio network, a base station controls and supports a set of fixed-location wireless subscribers. The objective is to maximize the throughput of the cognitive network while not affecting the performance of primary users. Both downlink and uplink transmission scenarios in the cognitive network are considered. For both scenarios, we propose two-phase mixed distributed/centralized control algorithms that require minimal cooperation between cognitive and primary devices. In the first phase, a distributed power updating process is employed at the cognitive and primary nodes to maximize the coverage of the cognitive network while always maintaining the constrained signal to interference plus noise ratio of primary transmissions. In the second phase, centralized channel assignment is carried out within the cognitive network to maximize its throughput. Numerical results are obtained for the behaviors and performance of our proposed algorithms.

A Q-learning based approach to interference avoidance in self-organized femtocell networks

Abstract: The femtocell concept is an emerging technology for deploying the next generation of the wireless networks, aiming at indoor coverage enhancement, increasing capacity, and offloading the overlay macrocell traffic. Nevertheless, the detrimental factor in such networks is co-channel interference between macrocells and femtocells, as well as among neighboring femtocells. This in turn can dramatically decrease the overall capacity of the network. In addition, due to their non-coordinated nature, femtocells need to self-organize in a distributed manner not to cause interference on the macrocell, while at the same time managing interference among neighboring femtocells. This paper proposes and analyzes a Reinforcement-Learning (RL) framework where a macrocell network is underlaid with femtocells sharing the same spectrum. A distributed Q-learning algorithm is proposed in which each Femto Base Station/Access Point (FBS/FAP) gradually learns (by interacting with its local environment) through trials and errors, and adapt the channel selection strategy until reaching convergence. The proposed Q-learning algorithm is cast into high level and low level subproblems, in which the former finds in a decentralized way the channel allocation through Q-learning, while the latter computes the optimal power allocation. Investigations show that through learning, femtocells are not only able to self-organize with only local information, but also mitigate their interference towards the macrocell network.

Ring-Walk Based Channel-Hopping Algorithms with Guaranteed Rendezvous 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 central controller and common control channel (CCC). We propose a jump-stay based 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. Compared with the existing CH algorithms, our algorithm achieves the following advances: i) guaranteed rendezvous without the need of time-synchronization; ii) applicability to rendezvous of multi-user and multi-hop scenarios. We derive the maximum time-to-rendezvous (TTR) and the upper-bound of expected TTR of our algorithm for both 2-user and multi-user scenarios (shown in Table I). Extensive simulations are further conducted to evaluate performance of our algorithm.

Dogfight in Spectrum: Combating Primary User Emulation Attacks in Cognitive Radio Systems—Part II: Unknown Channel Statistics

Abstract: In cognitive radio systems, primary user emulation (PUE) attack means that an attacker sends primary-user-like signals during the spectrum sensing period such that honest secondary users leave the corresponding channels, which causes a serious threat to cognitive radio systems. A passive anti-PUE approach, similar to the random frequency hopping in traditional anti-jamming schemes, is proposed and called dogfight in spectrum. In this scheme, the defenders randomly choose channels to sense and avoid the PUE attack. It is assumed that the channel statistics like availability probabilities are known; then the PUE attack and the random hopping are modeled as a zero-sum game between the attacker and defending secondary user(s). The Nash equilibrium of the game is found. The anti-jamming efficiency is also obtained. Numerical simulations demonstrated the performances of the proposed schemes for both the single defender, multiple defender and multiple round cases.

Downlink Spectrum Sharing for Cognitive Radio Femtocell Networks

Abstract: Femtocell is envisioned as a highly promising solution for indoor wireless communications. The spectrum allocated to femtocells is traditionally from the same licensed spectrum bands of macrocells. In this case, the capacity of femtocell networks is highly limited due to the finite number of licensed spectrum bands and also the interference with macrocells and other femtocells. In this paper, we propose a radically new communication paradigm by incorporating cognitive radio in femtocell networks. The cognitive radio enabled femtocells are able to access spectrum bands not only from macrocells but also from other licensed systems (e.g. TV systems) provided the interference from femtocells to the existing systems is not harmful. It results in more channel opportunities for femtocells. Thus, the co-channel interference in femtocells can be greatly reduced and the network capacity can be significantly improved. Because of the difference from other traditional wireless networks, we argue the traditional spectrum sharing schemes such as coloring methods are not efficient to femtocell networks especially for dense deployment scenarios. We formulate the downlink spectrum sharing problem in cognitive radio femtocell networks, and employ decomposition theories to solve the problem. Simulation results indicate that cognitive radio enabled femtocells could achieve much higher capacity than the femtocell networks which do not employ agile spectrum access. Simulation results also show that our proposed scheme without any iteration can achieve almost twice of the average capacity by coloring method when the number of available channels is less than five. Moreover, our proposed scheme can converge very fast with a typical value of only five iterations, and it can achieve around two percent extra average capacity than the fixed power control scheme.

FlashLinQ: A synchronous distributed scheduler for peer-to-peer ad hoc networks

Abstract: This paper proposes FlashLinQ - a synchronous peer-to-peer wireless PHY/MAC network architecture for distributed channel allocation. By leveraging the fine-grained parallel channel access of OFDM, FlashLinQ develops an analog energy-level based signaling scheme that enables SIR (Signal to Interference Ratio) based distributed scheduling. This new signaling mechanism and the corresponding allocation algorithms permit efficient channel-aware spatial resource allocation, leading to significant gains over a CSMA/CA system with RTS/CTS. FlashLinQ is a complete system architecture including (i) timing and frequency synchronization derived from cellular spectrum, (ii) peer discovery, (iii) link management, and (iv) channelaware distributed power, data-rate and link scheduling. We implement FlashLinQ over licensed spectrum on a DSP/FPGA platform. In this paper, we present performance results for FlashLinQ using both implementation and simulations.

Efficient Multicast Algorithms for Multichannel Wireless Mesh Networks

Abstract: The wireless mesh network is an emerging technology that provides high quality service to end users as the "last milerdquo of the Internet. Furthermore, multicast communication is a key technology for wireless mesh networks. Multicast provides efficient data distribution among a group of nodes. However, unlike other wireless networks, such as sensor networks and MANETs, where multicast algorithms are designed to be energy efficient and to achieve optimal route discovery among mobile nodes, wireless mesh networks need to maximize throughput. This paper proposes two multicast algorithms: the level channel assignment (LCA) algorithm and the multichannel multicast (MCM) to improve the throughput for multichannel and multi-interface mesh networks. The algorithms build efficient multicast trees by minimizing the number of relay nodes and total hop count distances of the trees. The algorithms use dedicated channel assignment strategies to reduce the interference to improve the network capacity. We also demonstrate that using partially overlapping channels can further diminish the interference. Furthermore, additional interfaces help to increase the bandwidth, and multiple gateways can further shorten the total hop count distance. Simulations show that those algorithms greatly outperform the single-channel multicast algorithm. We also observe that MCM achieves better throughput and shorter delay while LCA can be realized in distributed manner.

Relay selection and power allocation in cooperative cellular networks

Abstract: We consider a system with a single base station communicating with multiple users over orthogonal channels while being assisted by multiple relays. Several recent works have suggested that, in such a scenario, selection, i.e., a single relay helping the source, is the best relaying option in terms of the resulting complexity and overhead. However, in a multiuser setting, optimal relay assignment is a combinatorial problem. In this paper, we formulate a related convex optimization problem that provides an extremely tight upper bound on performance and show that selection is, almost always, inherent in the solution. We also provide a heuristic to find a close-to-optimal relay assignment and power allocation across users supported by a single relay. Simulation results using realistic channel models demonstrate the efficacy of the proposed schemes, but also raise the question as to whether the gains from relaying are worth the additional costs.

A Two-Step Approach to Power Allocation for OFDM Signals Over Two-Way Amplify-and-Forward Relay

Abstract: A two-way relay channel (TWRC) in which two terminals T 1 and T 2 exchange orthogonal frequency division multiplexing (OFDM) signals with the help of an amplify-and-forward (AF) relay T 3 is considered here, and an efficient technique for allocating powers to N parallel tones of OFDM is developed. A sum rate maximization problem is formulated by replacing the individual power constraints of the conventional sum rate maximization problem, which limit the power of each terminal, with the total power constraint limiting the sum of powers of all terminals. The maximization problem with the total power constraint yields a more efficient power allocation policy than the conventional problem with individual power constraints. It is shown that the closed-form solution of the maximization problem under the total power constraint can be obtained for a single-tone system (N=1). Based on this result, a two-step suboptimal approach is proposed in which the power is optimally assigned to each tone first, and then at each tone the assigned power is distributed to the three terminals. The proposed method is shown to assign 50% of the total power to relay T 3 irrespective of the channels. It is demonstrated that the proposed method is considerably simpler to implement than the conventional dual-decomposition method (DDM), yet the performance of the former is almost identical to that of the latter.

Multichannel dynamic frequency selection

Abstract: Multichannel dynamic frequency selection in wireless networks begins with an access point for a wireless network broadcasting a list of unused channels that are available for communication within the area served by the access point. The various access terminals within this service area receive the broadcast and measure various interference characteristics of each of the channels in the list. The access terminals then send this interference information to the access point, which compiles a matrix of interference information that is associated with the quality of each signal as related to each access terminal. Using this information, the access point selects the appropriate channels to serve the most number of access terminals at the highest possible channel qualities.

Multi-dimensional Conflict Graph Based Computing for Optimal Capacity in MR-MC Wireless Networks

Abstract: Optimal capacity analysis in multi-radio multi-channel wireless networks by nature incurs the formulation of a mixed integer programming, which is NP-hard in general. The current state of the art mainly resorts to heuristic algorithms to obtain an approximate solution. In this paper, we propose a novel concept of multi-dimensional conflict graph (MDCG). Based on MDCG, the capacity optimization issue can be accurately modeled as a linear programming (LP) multi-commodity flow (MCF) problem, augmented with maximal independent set (MIS) constraints. The MDCG-based solution will provide not only the maximum throughput or utility, but also the optimal configurations on routing, channel assignment, and scheduling. Moreover, the MDCG-based optimal capacity planning can exploit dynamic channel swapping, which is difficult to achieve for those existing heuristic algorithms. A particular challenge associated with the MDCG-based capacity analysis is to search exponentially many possible MISs. We theoretically show that in fact only a small set of critical MISs, termed as critical MIS set, will be scheduled in the optimal resource allocation. We then develop a polynomial computing method, based on a novel scheduling index ordering (SIO) concept, to search the critical MIS set. Extensive numerical results are presented to demonstrate the efficiency of the MDCG-based resource allocation compared to well-known heuristic algorithm presented in [1], and the efficiency of SIO-based MIS computing compared to the widely adopted random algorithm for searching MISs.

A cognitive radio system for e-health applications in a hospital environment

Abstract: Wireless communications technologies are used to support a variety of electronic health applications to transfer medical data and patient information. However, using wireless communications technology in a healthcare environment poses two major challenges. First, the electromagnetic interference caused to bio-medical devices by wireless devices could critically affect their performance. Second, since different types of e-health applications have different priorities, access to the wireless channel by the corresponding devices needs to be prioritized. In this article we introduce a novel cognitive-radio-based approach to address these challenges in wireless communications for e-health applications in a hospital environment. First, the requirements for a wireless communications system to be used in a healthcare environment are identified, and potential applications of cognitive radio technology for e-health applications are discussed. Then a cognitive radio system is proposed for e-health applications in a hospital environment, which protects the medical devices from harmful interference by adapting the transmit power of wireless devices based on EMI constraints. An EMI-aware handshaking protocol is proposed for channel access by two different types of applications with different priorities. The performance of this cognitive radio system for e-health applications is evaluated through simulations.

Efficient Recovery Control Channel Design in Cognitive Radio Ad Hoc Networks

Abstract: A constantly available control channel facilitates control message exchange and spectrum coordination in cognitive radio (CR) ad hoc networks. When a dedicated control channel is unavailable, a control channel must be dynamically allocated in licensed channels and vacated for the presence of primary users (PUs). As a result, the establishment of such a control channel is a challenge. In this paper, an efficient recovery control channel (ERCC) design is proposed to address this challenge. This heuristic and distributed design approach is essentially based on the observed spectrum homogeneity in a neighborhood. By adaptively updating a list of channels commonly available to neighbors, each secondary user is able to efficiently establish new control channels among neighbors in response to PU activity changes. Therefore, a virtually “always on” control channel robust to PU activity can be realized by the proposed method. The contributions are summarized as follows: 1) The proposed method efficiently recovers control channels from PU activity changes and maintains network connectivity. 2) It extends the control channel coverage to facilitate broadcast and reduce control overhead and delay. 3) It minimizes the interference with PUs. Simulation results show that the proposed solution outperforms the classic group- and sequence-based solutions in the responsiveness to rapidly changing PU activity and the maintenance of connectivity. Furthermore, the increase in control channel coverage and the allocation of the highest quality channels to control channels can be well balanced with reliability and scalability in various network scenarios.

Optimal Relay Station Placement in Broadband Wireless Access Networks

Abstract: To satisfy the stringent requirement of capacity enhancement in wireless networks, cooperative relaying is envisioned as one of the most effective solutions. In this paper, we study the capacity enhancement problem by way of relay stations (RSs) placement to achieve an efficient and scalable design in broadband wireless access networks. To fully exploit the performance benefits of cooperative relaying, we develop an optimization framework to maximize the capacity as well as to meet the minimal traffic demand by each subscriber station (SS). In specific, the problem of joint RS placement and bandwidth allocation is formulated into a mixed-integer nonlinear program. We reformulate it into an integer linear program which is solvable by CPLEX. To avoid exponential computation time, a heuristic algorithm is proposed to efficiently solve the formulated problem. Numerical analysis is conducted through case studies to demonstrate the performance gain of cooperative relaying and the comparison between the proposed heuristic algorithm against the optimal solutions.

Spectrum auction framework for access allocation in cognitive radio networks

Abstract: In cognitive radio networks, there are two categories of networks on different channels: primary networks, which have high-priority access, and secondary networks, which have low-priority access. We develop an auction-based framework that allows networks to bid for primary and secondary access based on their utilities and traffic demands. The bids are used to solve the access allocation problem, which is that of selecting the primary and secondary networks on each channel either to maximize the auctioneer's revenue or to maximize the social welfare of the bidding networks, while enforcing incentive compatibility. We first consider the case when the bids of a network depend on which other networks it will share channels with. When there is only one secondary network on each channel, we design an optimal polynomial-time algorithm for the access allocation problem based on reduction to a maximum matching problem in weighted graphs. When there can be two or more secondary networks on a channel, we show that the optimal access allocation problem is NP-complete. Next, we consider the case when the bids of a network are independent of which other networks it will share channels with. We design a polynomial-time dynamic programming algorithm to optimally solve the access allocation problem when the number of possible cardinalities of the set of secondary networks on a channel is upper-bounded. Finally, we design a polynomial-time algorithm that approximates the access allocation problem within a factor of 2 when the above upper bound does not exist.

A Joint Power and Subchannel Allocation Scheme Maximizing System Capacity in Indoor Dense Mobile Communication Systems

Abstract: Indoor mobile communication systems (or simply indoor systems) are expected to yield significant improvement of capacity and coverage at low cost on mobile communication systems. However, the indoor system will likely be in dense environments, in which many cells exist in a small region, and a great portion of the coverage of a cell is overlapped by that of other cells. In dense environments, the systems are exposed to strong intercell interference, which is critical to system performance and should be mitigated by a novel radio resource management (RRM) scheme. In this paper, we first derive the characteristics of an optimal allocation of power and subchannel in dense environments. We prove that a special form of power allocation, which is called binary power allocation, in which only one transmitter transmits a signal for each subchannel, performs better than power allocation by conventional schemes. Then, we propose an efficient scheme for jointly allocating power and a subchannel based on the binary power allocation. Simulation and numerical results show that the proposed scheme can achieve larger system capacity than conventional schemes.

Cyclic Prefix Design and Allocation in Bit-Loaded OFDM over Power Line Communication Channels

Abstract: The usual approach when designing an orthogonal frequency division multiplexing (OFDM) system, is to dimension the length of the cyclic prefix (CP) equal to the length of a typical "bad" (i.e., long) channel impulse response, so that both inter-symbol and inter-carrier interference are avoided for almost all channel realizations. However, such an approach does not maximize system capacity. It (a) wastes channel resources for relatively short channel impulse response realizations and (b) it is not necessarily optimal to completely eliminate interference. In this paper, we study the problem of designing the CP length for OFDM systems in a capacity-optimal way. To this end, we first present optimal and simplified metrics suitable to maximize capacity. Then, we apply those metrics and propose practical resource (bit-loading and OFDM sub-channel assignment) algorithms that include CP-length adaptation. We present numerical results for the example of a power line communication (PLC) OFDM system with typical indoor PLC channels that confirm the gains achievable with the proposed CP-length adaptation.

Cooperative adaptive spectrum sharing in cognitive radio networks

Abstract: The cognitive radio (CR) paradigm calls for open spectrum access according to a predetermined etiquette. Under this paradigm, CR nodes access the spectrum opportunistically by continuously monitoring the operating channels. A key challenge in this domain is how the nodes in a CR network (CRN) cooperate to access the medium in order to maximize the CRN throughput. Typical multichannel MAC protocols assume that frequency channels are adjacent and that there are no constraints on the transmission power. However, a CRN may operate over a wide range of frequencies, and a power mask is often enforced on the transmission of a CR user to avoid corrupting the transmissions of spectrum-licensed primary-radio (PR) users. To avoid unnecessary blocking of CR transmissions, we propose a novel distance-dependent MAC protocol for CRNs. Our protocol, called DDMAC, attempts to maximize the CRN throughput. It uses a novel probabilistic channel assignment mechanism that exploits the dependence between the signal's attenuation model and the transmission distance while considering the traffic profile. DDMAC allows a pair of CR users to communicate on a channel that may not be optimal from one user's perspective, but that allows more concurrent transmissions to take place, especially under moderate and high traffic loads. Simulation results indicate that, compared to typical multichannel CSMA-based protocols, DDMAC reduces the blocking rate of CR requests by up to 30%, which consequently improves the network throughput.

Fractional frequency reuse and interference suppression for OFDMA networks

Abstract: The downlink performance of cellular networks is known to be strongly limited by inter-cell interference. In order to mitigate this interference, a number of frequency reuse schemes have recently been proposed. This paper discusses a novel fractional frequency reuse (FFR) scheme combined with interference suppression for orthogonal frequency division multiple access (OFDMA) networks, which are currently being considered in LTE-A and WiMAX IEEE 802.16m standardization processes. We confine to the case of cell edge users and show that the novel FFR scheme improves the spectral efficiency by allowing one out-of-cell interference. Then the proposed subcarrier and rate allocation ensures interference exploitation by the mobile station (MS) which results in the reduction of power consumption at the base stations (BSs). Interestingly no inter-cell interference coordination but only a priori frequency planning is required in the proposed scheme.

Optimization of OFDMA-Based Cellular Cognitive Radio Networks

Abstract: In this paper, we study the coexistence and optimization of a multicell cognitive radio network (CRN) which is overlaid with a multicell primary radio network (PRN). We propose a PRN-willingness-based design framework for coexistence and subchannel sharing, and a Lagrange duality based technique to optimize the weighted sum rate (WSR) of secondary users (SUs) over multiple cells. First, to avoid unacceptable SU interference to primary users (PUs), the PRN determines its interference margin based on its target performance metric and channel conditions, and broadcasts this information to the CRN. Second, each CRN cell optimizes its WSR and implements intercell iterative waterfilling (IC-IWF) to control the intercell interference. To account for the interference and transmit power limits at SUs, multilevel waterfilling (M-WF) and direct-power truncation (DPT) duality schemes are developed. Third, we develop a serial dual update technique which enables low-complexity and fast-convergence of the proposed duality schemes. Numerical results demonstrate the effects of multiple parameters, such as the number of SUs per cell, subchannel occupancy probability (SOP), and outage probability of the PUs. Our results show that the proposed duality schemes provide a large performance enhancement than the channel-greedy and access-fairness based resource allocation schemes.

Channel management in IEEE 802.22 WRAN systems

Abstract: Channel management policy is one of the key functions of any cognitive radio system. The channel management decision in a cognitive radio system depends on various factors such as government regulations, limitations of transmission power between communicating devices, availability of geo-location information, and the quality of various available channels. The main purpose of channel management in a cognitive radio system is to protect the incumbent users (licensed users). The first international standard based on cognitive radio technology is IEEE 802.22, Wireless Regional Area Networks, which aims at providing broadband access in rural areas by effectively utilizing the unused TV channels. This standard aims at describing both PHY and MAC layer functionalities in an infrastructure- based broadband wireless access network for communication between consumer premises equipment using a base station. This article presents the cognitive radio functionality of this standard in detail. The cognitive functionality is provided by the dynamic channel management using channel sensing, channel classification, and maintenance of channel information. Using these techniques, this standard effectively protects the incumbent users and dynamically manages the channel allocation in IEEE 802.22 WRAN systems.

QoS aware relay selection and subcarrier allocation in cooperative OFDMA systems

Abstract: Most existing works on resource allocation in cooperative OFDMA systems have focused on homogeneous users with same service and demand. In this letter, we investigate relay selection and subcarrier allocation in a cooperative OFDMA system with considerations of QoS guarantees and service support. By introducing QoS price, this combinatorial problem with exponential complexity is converted into a convex one, and a dual based QoS-aware schedule (QAS) algorithm is proposed to tackle the problem. Simulation results reveal that our proposed algorithm significantly outperforms previous works in terms of both services support and QoS satisfaction.

Resource Allocation in Multi-cell OFDMA-based Relay Networks

Abstract: Cooperative relay networks combined with Orthogonal Frequency Division Multiplexing Access (OFDMA) technology has been widely recognized as a promising candidate for future cellular infrastructure due to the performance enhancement by flexible resource allocation schemes. The majority of the existing schemes aim to optimize single cell performance gain. However, the higher frequency reuse factor and smaller cell size requirement lead to severe inter-cell interference problem. Therefore, the multi-cell resource allocation of subcarrier, time scheduling and power should be jointly considered to alleviate the severe inter-cell interference problem. In this paper, the joint resource allocation problem is formulated. Considering the high complexity of the optimal solution, a two-stage resource allocation scheme is proposed. In the first stage, all of the users in each cell are selected sequentially and the joint subcarrier allocation and scheduling is conducted for the selected users without considering the interference. In the second stage, the optimal power control is performed by geometric programming method. Simulation results show that the proposed the interference-aware resource allocation scheme improves the system capacity compared with existing schemes. Especially, the edge users achieve more benefit.

Optimal Cooperative Internetwork Spectrum Sharing for Cognitive Radio Systems With Spectrum Pooling

Abstract: Spectrum pooling in cognitive radio systems is an approach to manage the available spectrum bands from different licensed networks. Most previous work on spectrum pooling concentrates on the system architecture and the design of flexible-access algorithms and schemes. In this paper, we present a cooperative scheme for internetwork spectrum sharing among multiple secondary systems, which takes into account the price and spectrum efficiency as the design criteria. Specifically, the spectrum-sharing problem is formulated as a stochastic bandit system; thus, the optimal spectrum-sharing scheme is simply allocating the new available band to the secondary network with the lowest index. Extensive simulation examples illustrate that the proposed scheme significantly improves the performance compared with the existing scheme that ignores optimal spectrum sharing.