Optimizing SU Transmission Time Under Collision Constraint Considering PU Returns

Cognitive radio methodologies have the potential to dramatically increase the throughput of wireless systems. Herein, control strategies which enable the superposition in time and frequency of primary and secondary user transmissions are explored in contrast to more traditional sensing approaches which only allow the secondary user to transmit when the primary user is idle. In this paper, the optimal transmission policy for the secondary user when the primary user adopts a retransmission-based error control scheme is investigated. The policy aims to maximize the secondary users' throughput, with a constraint on the throughput loss and failure probability of the primary user. Due to the constraint, the optimal policy is randomized, and determines how often the secondary user transmits according to the retransmission state of the packet being served by the primary user. The resulting optimal strategy of the secondary user is proven to have a unique structure. In particular, the optimal throughput is achieved by the secondary user by concentrating its transmission, and thus its interference to the primary user, in the first transmissions of a primary user packet. The rather simple framework considered in this paper highlights two fundamental aspects of cognitive networks that have not been covered so far: 1) the networking mechanisms implemented by the primary users (error control by means of retransmissions in the considered model) react to secondary users' activity; 2) if networking mechanisms are considered, then their state must be taken into account when optimizing secondary users' strategy, i.e., a strategy based on a binary active/idle perception of the primary users' state is suboptimal.

In cognitive radio networks, secondary users need to access the licensed spectrum while neither disturbing the transmissions of the primary users nor introducing much interference to other secondary users. Hence, proper power controlling is of paramount importance to ensure efficient system operation. The previous work on power control in cognitive networks mainly focuses on the interactions among a set of secondary users. The primary users' influence is rarely considered. In this paper, a new power control game model is formulated, by including the primary users into the player set of the game. The primary users are rewarded for sharing their licensed spectrum with secondary users by setting a reasonable interference cap for the secondary transmissions. However, we ensure a minimum required Quality of Service (QoS) for primary users by severely penalizing their utility if their required transmission quality is not met. Simultaneously, the secondary users achieve energy efficient transmissions while not introducing much interference to both the primary and other secondary users. We prove that the proposed cognitive power control game has a unique Nash equilibrium (NE). The numerical examples show that the proposed game theoretical power control algorithm can provide the secondary users with energy efficient transmissions and the primary users with reasonable monetary rewards, while not compromising their required QoS.

We investigate opportunistic cooperation between secondary (unlicensed) users and primary (licensed) users in cognitive radio networks. We consider two models for such cooperation. In the first model, called the Cooperative Relay Model, a secondary user cannot transmit its own data concurrently with a primary user. However, it can employ cooperative relaying in order to improve the effective transmission rate of the primary user. In the second model, called the Interference Model, a secondary user is allowed to transmit its data concurrently with a primary user. However, the secondary user can “cooperate” by deferring its transmissions when the primary user is busy. In both models, the secondary users must make intelligent cooperation decisions as they seek to maximize their own throughput subject to average power constraints. The decision options are different during idle and busy periods of the primary user, and the decisions in turn influence the durations of these periods according to a controllable infinite state Markov chain. Such problems can be formulated as constrained Markov decision problems, and conventional solution techniques require either extensive knowledge of the system dynamics or learning based approaches that suffer from large convergence times. However, using a generalized Lyapunov optimization technique, we design a novel greedy and online control algorithm that overcomes these challenges. Remarkably, this algorithm does not require any knowledge of the network arrival rates and is provably optimal.

We consider a cooperation scenario between primary users and untrusted secondary users in cognitive radio networks. The secondary users are willing to help the primary users to relay the primary users' messages in reward for being allowed to share the primary users' spectrum bands. However, the primary users might be reluctant to accept this help, since the secondary users are untrustworthy and may try unauthorized decoding of the primary users' messages. This paper will answer the question: when is this cooperation mutually beneficial for primary and secondary users? Taking an approach of information-theoretic secrecy, such as coding techniques for wiretap channels, the primary users can allow the secondary users to sense and relay the message, while ensuring that the secondary users are ignorant of the primary users' messages. We characterize an achievable secrecy rate of primary users with a rate of the secondary users' communication. From the derived rate pairs, an optimization problem is formulated such that the secondary transmitter distributes its transmit power to maximize its data rate while providing a higher secrecy rate to the primary users. We demonstrate that this cooperation can provide a positive secrecy rate, even when a non-cooperative scheme achieves a zero secrecy rate.

Dynamic spectrum access has been proposed to address the spectrum scarcity. Based on this access mode, secondary users are allowed to opportunistically operate when primary users are absent. Secondary Users are, however, required to relinquish the spectrum upon return of the incumbent spectrum holder. Although it improves spectrum utility, opportunistic spectrum access limits secondary users' access to exogenous spectrum holes vacated by primary users. We argue that spectrum holes should be endogenous, enabled by incentives to incumbent users to increase spectrum availability, while mitigating risk. To this end, we take a different perspective on dynamic spectrum sharing and propose a coopetive framework, whereby primary and secondary users engage in a cooperative, yet competitive, auction-driven spectrum sharing to enhance spectrum usage. In this framework, the primary users'spectrum is organized in three bands, namely exclusive usage, usage right and management right bands. Based on this structure, spectrum is traded as financial options to increase trading flexibility and capture the value primary and secondary users attach to spectrum access and usage. Spectrum trading between primary and secondary users is formalized as a utility maximization problem. Approximate solutions to this problem are derived and their performance is analyzed. The results show that spectrum trading, which combines revocable and exclusive leasing, provides higher utilities for both primary and secondary users.

Although cognitive radio technology improves efficiency of spectrum utilization, primary users usually do not gain from opening up the spectrum in the opportunistic spectrum access, and sometimes even suffer from collisions due to secondary users' imperfect spectrum sensing. However, in this paper, we show that if information secrecy is a concern, primary users could actually be better off by allowing secondary users to cooperatively share the spectrum. Specifically, we propose a new cooperation paradigm in cognitive radio networks that primary users improve secrecy with the help of trustworthy secondary users, in the presence of an intelligent and passive eavesdropper attempting to decode primary users' messages. After deriving the achievable pair of primary users' secrecy rate and secondary users' transmission rate under various circumstances, we model the interaction between primary users and secondary users as a Stackelberg game in which transmission power levels are the key to maximize data rates. Moreover, based on a 2-D representation of how achievable rates depend on power-level regions, we apply equilibrium analysis to understand the optimal strategy of primary and secondary users. Finally, simulation results are presented to verify the performance.

The cooperation among the secondary users or among the secondary users and the primary users have proven to bring many benefits to both primary and secondary users in cognitive radio networks. In this paper, cooperative relaying in cognitive radio networks is studied for rateless coding error-control mechanism. For a pair of primary transmitter and receiver, we find the region in which any secondary or cognitive user can cooperate with the primary user in a constructive way. A queueing theoretical model is employed to describe the underlying system parameters and to create a mathematical framework for the analysis. The throughput performance of the secondary users is maximized based on the input traffic of the primary users. Using the unique properties of rateless codes, a low-complexity relay selection mechanism is also introduced. Through the experimental analysis, we show that the proposed rateless-coding-based cooperative mechanism can perform similar to the more complicated and more costly selective-repeat automatic repeat request algorithm. The numerical analysis using the Rapid Analysis of Queueing Systems (RAQS) software package is provided to support the findings.

In cognitive radio networks (CRNs), secure information transfer is of paramount importance for primary users (PUs), while secondary users (SUs) mainly desire to ease the starvation for transmission opportunities. To meet such different requirements, cooperation between PUs and SUs can be leveraged and therefore create a win-win situation. In this paper, we investigate cooperative spectrum access for CRNs, which targets to improve the secure transmission of PUs via cooperating SUs that would be incented by certain transmission opportunities. Two types of cooperation schemes are proposed, whereby the PU either cooperates with two individual SUs or a cluster of SUs, which are referred to as relay-jammer (R-J) scheme and cluster-beamforming (C-B) scheme, respectively. In R-J scheme, two individual SUs act as a relay and a friendly jammer to improve the PU's secrecy; In return, the PU allocates a fraction of access time for the SUs' transmission. To achieve the maximum secrecy rate, joint time and power allocation is considered. Particularly, the cooperating relay and jammer determine the optimal transmission power, while the PU decides the optimal time allocation strategy. In C-B scheme, the PU cooperates with a cluster of SUs to enhance the secrecy of the primary link via collaborative beamforming, where three different approaches are proposed for the scenarios with one eavesdropper, with multiple eavesdroppers, and without eavesdroppers' information, respectively. To maximize the secrecy rate, the weight selection and time allocation are also studied. Simulation results are given to validate the proposed schemes and demonstrate that the PU can significantly enhance the secrecy through cooperation.

Much work has been done in the area of cognitive radio networks to formulate the inherent tradeoff among different metrics, such as sensing and throughput. Primary user (PU) traffic behavior can affect the mentioned tradeoff and must be considered in analyses, especially when cognitive users coexist with the dynamic-traffic PU. In this case, PU-returns to the spectrum during secondary users' (SUs) transmission are more likely and, hence, such kinds of interference are inevitable. Furthermore, how to model the PU traffic is important. Note that there are two kinds of interference between SU and PU in cognitive radio networks, one due to sensing error and the other due to primary user reoccupancy. In this paper, a new metric called energy per successful transmission time is defined to address both kinds of inference by formulating SUs' successful transmission time as well as energy consumption. Furthermore, collision probability and average packet delay are formulated considering these interference metrics and the primary user traffic is modeled as an alternating phase type renewal process by which many traffic behaviors, such as long range dependency and self-similarity can be modeled. Finally, some numerical examples are given and the corresponding curves for different metrics are discussed.

Spectrum sensing ranks amongst cognitive radio's most critical and demanding activities. For radio resource networks to use idle licensed bandwidth, secondary users need to identify the primary user's signal precisely. Cognitive radio networks (CRNs) have been proposed to improve the efficiency of spectrum use to meet the increasing demand for wireless bandwidth; they allow channel communication between secondary (unlicensed) and primary (licensed) users without interruption. A secondary user in a CRN must at all times track the presence of a primary user's signal to prevent the primary user (PU) from attempting to intervene whether the statistical variance of the PU data traffic would boost the prediction outcome provided by multiple current teaching algorithms in estimating the PU's average OFF time and the need for the best adaptive learning to predict accurate PU activities. The objective of the work has been modeled to identify the PUs signal. First, the data has been created via quadrature phase shift keying modulation and quadrature amplitude modulation by convolutional neural network (CNN). A dataset with different orthogonal frequency‐division (OFDM) multiple access signals is generated. Then cyclo‐stationary functions are extracted using the accumulation process fast Fourier Transform. This research aims to use glow worm swarm optimization (GWSO) to automatically check for the optimal design of CNNs without any manual work being required. Also, k‐Nearest Neighbors (kNN) replaces Softmax, as it outperforms conventional CNN architectures with noisy signals. A comparison of the proposed classifier with another machine learning classifier, namely support vector machine, Decision tree (DT), clearly shows that SVM and DT are outperformed by the improved convolution neural network‐glow worm swarm optimization (ICNN‐GWSO) classification. Results of simulation show that the improved scheme outperforms conventional spectrum sensing systems, both in fading and non‐fading settings, where efficiency is measured using measures such as chance, the total likelihood of error, and the ability to optimize data transfer possibilities.

The spectrum scarcity problem can be tackled by promoting a more efficient use of the radio spectrum. Spectrum sharing techniques like TV White Spaces (TVWS), Licensed Shared Access (LSA), and Spectrum Access System (SAS), are adequate solutions for this problem and there exist already regulation and standardization efforts worldwide. To evaluate the coexistence between primary and secondary spectrum users, a Long Term Evolution (LTE) multi-cell simulator has been designed, which employs a generic spectrum sharing technique, Dynamic Spectrum Access (DSA), in order to obtain additional network capacity. As a way to bring attention and confidence of the telecommunications sector regarding the benefits that this technology may bring, the analysis is done in terms of interference suffered by incumbents (primary users) and capacity by secondary users. Results have confirmed the unfeasibility of co-channel coexistence for moderate distances between the cordless camera service (incumbent) and LTE network (secondary user) due to high interference. However, for adjacent bands, a gain of 40% in the secondary users’ capacity is possible following more restrictive interference protection requirements and 30% gain with the smaller frequency separation between primary and secondary operating frequencies.

This study deals with the scaling laws of ad hoc cognitive networks. In the network, m primary users and n secondary users ( m n ) are randomly located in the same geographic area and share one common frequency spectrum. By loosening some of the restrictions for the network, the authors obtained the throughput upper bounds for both primary and secondary users. To obtain the lower bounds (achievable throughputs), we proposed a cooperative transmission scheme between the primary and secondary users by using the percolation theory, and the results showed that the achievable throughputs can meet the upper bounds, thus, the authors obtained the throughputs. On the basis of our results, per primary user can transmit with a throughput of min(Θ(1), Θ(Θ n/m )), which is higher than the throughput of Θ(Θ1/ m ) in the cognitive network without cooperative relay. This may serve as a strong incentive for primary users to cooperative with secondary users. Meanwhile, secondary users can achieve the same scale as if there is no primary network exists.

In a cognitive radio ad hoc network (CRAHN), the secondary user node has a restricted range for sensing other users within the network. To enhance the performance of nodes (secondary and primary users) in a CRAHN, the problem of limited channel sensing range and interference should be reduced which would enable the simultaneous transmission of primary and secondary users. In this paper, a cooperative MAC (medium access control) protocol is proposed—MLCP, which exploits the concept of multichannel network, for obtaining high system throughput. The main purpose of the proposed protocol is to introduce cooperation among secondary users, using the common control channel. The presence of the primary user is detected and the information is shared among neighbouring secondary users within the network proactively. This protocol is simulated using Network Simulator 2 and analysed with respect to system throughput, packet delivery ratio, and end-to-end delay experienced by primary users. The performance of the proposed protocol is also compared with existing cooperative MAC protocol and non-cooperative MAC protocol network scenario.

In this paper we study the resources access problem in cognitive radio networks, especially we are interested in the large number of secondary users (SUs). We establish a model based on channel access process when the PU (Primary User) is active, respecting the level of interference authorized by the operator. We study a system of cooperation between the SUs and the PUs to increase the performance of the system. SUs pass through an negotiation phase with the PUs for the acquisition of the underutilized channels with exceeded interference caused to the PU. The PU will support additional interference Δ but will benefit from the cooperation of SUs to relay its data. We model this cooperation as coalitional game.The utility function depends on two main parameters which are: transmission power and noise level. A distributed coalition formation algorithm is also proposed, which can be used by SUs to decide whether to join or leave a coalition. Such a decision is based on whether it can increase the maximal coalition utility value. We consider also the trade off between energy efficiency and the target throughput in the proposed cooperative relay network. The objective of this work is to validate the expected enhancement of the overall throughput of the network and also the energy efficiency while increasing the opportunity for SUs to access the licensed spectrum owned by PUs.

Dynamic spectrum access techniques utilized in cognitive radio systems allow more efficient use of spectrum. In such systems, secondary users are supposed to operate in primary users' spectrum without interfering them. In this paper, we investigate an opportunistic spectrum sharing technique in cognitive radio networks for a special case in which, two secondary users are allowed to coexist in a channel (sub-banding). The sub-banding process in the proposed algorithm is such that, when all the channels are occupied by the primary and secondary users, then the secondary users' channels can be divided into two subbands, and two secondary users may use a sub-band, simultaneously. For performance evaluation, we have derived metrics such as blocking probability, dropping probability, and channel utilization, and then, the simulation results for the cases of using and not using sub-banding for the secondary users have been compared. It is observed that in a spectrum sharing system, channel sub-banding significantly reduces the blocking and dropping probabilities of the secondary users, with the cost of lower quality channels compared to the state without using sub-bands.