An Opportunity Downlink Interference Alignment Algorithm Based on Punch Scheduling in Cognitive Heterogeneous Networks

Due to irregular deployment of small base stations (SBSs), the interference in cognitive heterogeneous networks (CHNs) becomes even more complex; in particular, the uncertainty of spectrum mobility aggravates the interference context. In this case, how to analyze system capacity to obtain a closed-form expression becomes a crucial problem. In this paper we employ stochastic methods to formulate the capacity of CHNs and achieve a closed-form expression. By using discrete-time Markov chains (DTMCs), the spectrum mobility with respect to the arrival and departure of macro base station (MBS) users is modeled. Then an integral method is proposed to derive the interference based on stochastic geometry (SG). Also, the effect of sensing accuracy on network capacity is discussed by concerning false-alarm and miss-detection events. Simulation results are illustrated to show that the proposed capacity analysis method for CHNs can approximate the conventional sum methods without rigorous requirement for channel station information (CSI). Therefore, it turns out to be a feasible and efficient way to capture the network capacity in CHNs.

For a multiuser cognitive OFDM network, most existing adaptive resource allocation methods focus solely on fixed data-rate requirement (QoS guaranteed) or variable data-rate (no QoS guaranteed) conditions without any fairness consideration. In this paper, we investigate the resource allocation problem in a heterogeneous cognitive network with different QoS requirements. By decomposing the problem as a convex optimization, an optimal time-sharing resource allocation method is proposed to maximize the throughput of cognitive network under both subcarrier interference temperature limits and heterogeneous data-rate requirements. Finally, the performance of our proposed resource allocation algorithm is investigated by numerical results.

Cognitive radio and heterogeneous wireless networks are important candidate techniques for the fifth generation (5G) communication systems. On the other hand, propagation properties of radio channels in a physical layer are exploited to design efficient secure transmission schemes for 5G wireless networks. In this work, a security-aware joint power and subchannel allocation problem based on the inter-network cooperation is investigated at cognitive heterogeneous networks via imperfect spectral sensing. The security-aware joint power and subchannel allocation is subject to constraints in available subchannels, proportional fairness secrecy transmission rates among secondary mobile terminals (MTs), total interference power threshold, and total power for each secondary MT. In order to determine the impact of imperfect spectral sensing to resource allocation, we first represent the interference power at primary base station in terms of the misdetection probability and false alarm probability. Then, the security-aware power and subchannel allocation problem with inter-network cooperation is formulated as a biconvex optimization problem, and an optimal security-aware power and subchannel allocation algorithm is proposed utilizing the dual decomposition method. Compared to the heuristic power and subchannel allocation algorithms, numerical simulation results show that the proposed algorithms improve the total secrecy throughput and guarantee the proportional fairness among different secondary MTs.

Reducing the interference to the licensed mobile users and obtaining the energy efficiency are key issues in cognitive heterogeneous networks. A corresponding rate loss constraint is proposed to be used for the sensing-based spectrum sharing (SBSS) model in cognitive heterogeneous networks in this paper. Resource allocation optimization strategy is designed for the maximum energy efficiency under the proposed interference constraint together with average transmission power constraint. An efficiency algorithm is studied to maximize energy efficiency due to the nonconvex optimal problem. Furthermore, the relationship between the proposed protection criterion and the conventional interference constraint strategy under imperfect sensing condition for the SBSS model is also investigated, and we found that the conventional interference threshold can be regarded as the upper bound of the maximum rate loss that the primary user could tolerate. Simulation results have shown the effectiveness of the proposed protection criterion overcome the conventional interference power constraint.

With the rapid growth of network users, how to increase the system capacity has become an urgent problem for the current communication system in the case of limited spectrum resources. The introduction of multi-user systems has increased system capacity, but it has also led to inter-user interference, which has further affected system capacity. To solve the multi-user interference problem, interference alignment is introduced. Interference Alignment (IA) is an interference cancellation technique that effectively eliminates the effects of interfering signals by compressing the interfering signal into a space independent of the desired signal and then forcing the interfering signal to zero at the receiving end. However, in practical applications, interference-aligned transceivers require a joint design, which is often difficult to achieve. The traditional approach is to mathematically expect it, but it also leads to some degree of irrationality in the transceiver design. In this paper, based on the traditional least square interference alignment (LS-IA) algorithm, a symbol-detection-assisted least square interference alignment (SDA-LS-IA) algorithm is proposed for its shortcomings in transceiver algorithm design. Firstly, based on the precoding matrix and the zero-forcing matrix of the transceiver designed by the traditional LS-IA, the symbol detection is performed, and then the transceiver is designed again according to the detection symbol, and then the symbol detection is performed. The computer simulation proves that the proposed algorithm has better anti-interference performance than the traditional LS-IA.

How many small cell (SC) access points (APs) are required to guarantee a chosen quality of service in a heterogeneous network? In this chapter, we answer this question considering two different network models. The first is the downlink of a finite-area SC network where the locations of APs within the chosen area are uniformly distributed. A key step in obtaining the closed-form expressions is to generalize the well-accepted moment matching approximation for the linear combination of lognormal random variables. For the second model, we focus on a two-layer downlink heterogeneous network with frequency reuse-1 hexagonal macro cells (MCs), and SC APs that are placed at locations that do not meet a chosen quality of service from macro base stations (BSs). An important property of this model is that the SC AP locations are coupled with the MC coverage. Here, simple bounds for the average total interference within an MC makes the formulation possible for the percentage of MC area in outage, as well as the required average number of SCs (per MC) to overcome outage, assuming isolated SCs. Introduction Heterogeneous cellular networks (HCNs) are being considered as an efficient way to improve system capacity as well as effectively enhance network coverage [1, 2]. Comprising multiple layers of access points (APs), HCNs encompass a conventional macro cellular network (first layer) overlaid with a diverse set of small cells (SCs) (higher layers). Cell deployment is an important problem in heterogeneous networks, both in terms of the number and positioning of the SCs. Traditional network models are either impractically simple (such as the Wyner model [3]) or excessively complex (e.g., the general case of random user locations in a hexagonal lattice network [4]) to accurately model SC networks. A useful mathematical model that accounts for the randomness in SC locations and irregularity in the cells uses spatial point processes, such as Poisson point process (PPP), to model the location of SCs in the network [5–10]. The independent placement of SCs from the MC layer, has the advantage of analytical tractability and leads to many useful SINR and/or rate expressions. However, even assuming that wireless providers would deploy SCs to support mobile broadband services, the dominant assumption remains that SCs are deployed randomly and independent of the MC layer [11].

Cognitive Radio Network (CRN) is one of the emerging technologies to improve the spectrum utilization where Secondary Users (SUs) opportunistically uses the spectrum without creating significant interference to Primary Users (PUs). However, in CRN channel characteristics varies widely due to the random arrival of PUs which leads to call dropping/call blocking. Excessive call dropping reduces the quality of VoIP communication for SU's. Quality of Service (QoS) can be improved by exclusive channel reservation for SUs which involves policy formation and cost implication. To avoid the complexity, we have used sub-banding concept for Call Admission Control (CAC) scheme and utilized the scheme for VoIP applications using Adaptive Codec Switching Policy. Test bed analysis is performed to evaluate the behavior of some well known high/low bit rate codecs in CRN. Overall system performance is evaluated by using two dimensional Markov Model. Analysis shows that there is significant improvement in system capacity as probability of dropping and probability of blocking reduces. Finally Grade of Service (GoS) is considered as overall system performance metric which shows nearly 39% improvement under high SU traffic condition.

Cognitive Networks working on large scale are experimenting an increasing popularity. The interest, by both a scientific and commercial perspective, in the context of different environments, applications and domains is a fact. The natural convergence point for these heterogeneous disciplines is the need of a strong advanced technologic support that enables the generation of distributed observations on large scale as well as the intelligent process of obtained information. Focusing mostly on cognitive networks that generate information directly through sensor networks, existent solutions at level of metropolitan area are mainly limited by the use of obsolete/static coverage models as well as by a fundamental lack of flexibility respect to the dynamic features of the virtual organizations. Furthermore, the centralized view at the systems is a strong limitation for dynamic data processing and knowledge building.

The hierarchical macro/femto cell WiMAX networks are observed to be quite promising for mobile operators as it improves their network coverage and capacity at the outskirt of the macro cell. However, this new technology introduces increased number of macro/femto handoff which inturn may affect the system performance. Users moving with high velocity or undergoing real-time transmission suffers degraded performace due to huge number of unnecessary macro/femto handoff. Our proposed handoff decision algorithm eliminates the unnecessary handoff while balancing the load of the macro and femto cells. The performance of the proposed algorithm is analyzed using Continuous Time Markov Chain (CTMC) Model. In addition, we have also contributed a method to determine the balanced threshold level of the received signal strength (RSS) from macro base station (BS). The balanced threshold level provides equal load distribution to the macro and femto BSs. The balanced threshold level is evaluated based on the distant location of the femto cells for small scaled networks. Numerical analysis shows that threshold level above the balanced threhold results in higher load distribution to the femto BSs.KeywordsHierarchical WiMAX NetworksHandoffContinuous Time Markov ChainQoS ManagementLoad Balancing

This paper proposes a novel polarization-based underlay spectrum sharing scheme in cognitive heterogeneous cellular network (CHCN). Distinguished from traditional spectrum sharing exploiting spectrum opportunities in time, frequency, space and power domains, we exploit spectrum opportunities in polarization domain to enable small cell to coexist with macrocell. The proposed scheme optimizes the transmitting and receiving polarization states (PSs) of small cell to maximize the downlink capacity of small cell under the interference constraint of macrocell. Virtual polarization adaptation is adopted in small cell to generate the desired PSs by digital signal processing. Simulation results reveal the superiority of the proposed scheme in interference avoidance and spectrum efficiency improvement by exploiting polarization in CHCN.

SummaryCognitive heterogeneous network is a promising technology to meet the requirements of future wireless networks in cost and energy efficiency. By using vertical handover (VHO) between different network tiers, such as macro and femto, the traffic congestion can be potentially alleviated, and the spectral efficiency is significantly increased. However, performing VHO for a cognitive handover user (CHU) and simultaneously guaranteeing the quality of service of the primary user (PU) is the most challenging issue in such a network. This paper proposes an efficient VHO strategy in a cognitive heterogeneous network, which considers both adaptive average received signal and spectrum availability, namely, average received signal and spectrum availability. To analyse the performance of the proposed average received signal and spectrum availability algorithm, several metrics are investigated. First, the assignment probability of a CHU from a macro base station to a femto base station is evaluated and simplified in a closed‐form expression. Then, the outage probability of a CHU and collision probability of the PU are theoretically investigated for the proposed algorithm and are compared with 2 well‐known algorithms, the modified received signal strength–α and the received signal strength and wireless transmission loss. We also introduce a new performance metric, referred to as figure of merit, which jointly considers the assignment and outage probability of a CHU, collision probability of a PU, and the number of unnecessary handovers of a CHU. Figure of merit effectively shows the superiority of the proposed handover algorithm to conventional ones.

In this paper, we propose two distributed admission and power control (DAPC) algorithms for Device-to-Device (D2D) communication which share uplink resources with cellular system through cognitive radio techniques in underlay mode. In the presence of quality of service (QoS) protection (both for admitted D2D link (DL) and cellular link (CL)) and transmit power limit, the DAPC-Capacity algorithm is proposed with preference for the D2D system capacity, and the DAPC-Number algorithm is proposed with preference for the number of admitted DLs. Both the two algorithms try to determine if the new coming DL can be admitted in the system, and optimize powers of DLs to maximize the D2D system capacity. In proposed algorithms, each DL uses gradient descent method to update its transmit power, and the new coming DL and admitted DLs use different formulas to calculate gradients. In calculation of gradients, DLs cooperate with each other and only need to exchange "price" messages which indicate the effect of interference. Through the numerical results, we demonstrate the satisfying performance of proposed algorithms compared to traditional centralized algorithm.

In this paper we have studied the subcarrier and optimal power allocation strategy for OFDM-based cognitive radio (CR) networks. Firstly, in order to protect the primary user communication from the interference of the cognitive user transmissions in fading wireless channels, we design an opportunistic power control scheme to maximize the cognitive user capacity without degrading primary user's QoS. The mathematical optimization problem is formulated as maximizing the capacity of the secondary users under the interference constraint at the primary receiver and the Lagrange method is applied to obtain the optimal solution. Secondly, in order to limit the outage probability within primary user's tolerable range we analyze the outage probability of the primary user with respect to the interference power of the secondary user for imperfect CSI. Finally, in order to get the better tradeoff between fairness and system capacity in cognitive radio networks, we proposed an optimal algorithm of jointing subcarrier and power allocation scheme among multiple secondary users in OFDM-based cognitive radio networks. Simulation results demonstrate that our scheme can improve the capacity performance and efficiently guarantee the fairness of secondary users.

Cognitive Heterogeneous Networks

SUMMARYWith the introduction of low‐powered pico/femto‐base stations and relay nodes into the macro‐cell, recent heterogeneous networks provide an attractive approach for future wireless communication. Although it may achieve better coverage and higher capacity, several problems remain unsolved before practical deployment. For example, how to select the proper cell from neighbor low‐powered cells and then occupy the radio resource without interference on macro‐users is both important and challenging, especially for rigorous multimedia applications. The traditional cell access algorithms and quality‐control parameters such as delay or throughput no longer suit well in this complex environment. An effective approach should be pursued. In this paper, we investigate this interesting cell association problem and propose a complete green resolution on the basis of thorough discussions about the multimedia transmission under these concerns. Cognitive radio is introduced to share spectrum between macro‐cell and low‐powered cells while securing the transmission of authorized macro‐users. We also bring forth the concept of ‘interference balance’ to better manage the overall interference and energy consumption in the network. Restless bandit model is formulated on the basis of channel state, data rate, interference control, and the carefully chosen intra‐refreshing rate for multimedia traffic. Then the cell association scheme is designed to be efficient and practical because of the simple index property of our model output. Simulation results have proven the performance of our proposed resolution compared with existing algorithms on interference constraint, multimedia distortion, and overall network energy consumption balance. Copyright © 2013 John Wiley & Sons, Ltd.