Capacity Evaluation of LTE Network in Dynamic Spectrum Access and Interference Analysis

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.

A prototype Dynamic Spectrum Access (DSA) system is implemented, for ease of implementation, using the audio spectrum. In this setup, laptop PCs behave as two software defined radios (SDR), one a primary user (PU) and the other a secondary user (SU). The radios communicate digital information over the air, using the audio capabilities of standard soundcards. The PU, which is emulating the licensed user of an audio channel centered at 4 kHz, communicates using binary phase shift keying (BPSK) modulated data in periodic bursts. A cognitive radio (CR) based SU wishes to opportunistically occupy the PU channel during the inter-burst times, i.e. during the temporal ‘spectrum holes,’ while not interfering with the PU traffic. The PU link is implemented in MATLAB, while the SU is defined in GNU Radio with a separate Python control module defining its algorithm for spectrum sensing and hopping. The implementation of both communication links is described, as well as the initial performance evaluation of the preliminary system in terms of bit error rate performance of the PU with and without the presence of an active SU. The measured BER achieved for the best of the PU bursts with DSA was on the order of a few percent, just slightly higher than without DSA.

As the novel and effective approach to improving the utilization of the precious radio spectrum, cognitive radio technology is the key to realize the dynamic spectrum access (DSA) networks, where the secondary (unlicensed) users can opportunistically utilize the unused licensed spectrum in a way that confines the level of interference to the range the primary (licensed) users can tolerate. However, there are many new challenges associated with cognitive-radio-based DSA networks, such as the multi-channel hidden terminal problem and the fact that the time-varying channel availability differs for different secondary users, in the medium access control (MAC) layer. To overcome these challenges, we propose an efficient Cognitive Radio-EnAbled Multi-channel MAC (CREAM-MAC) protocol, which integrates the cooperative sequential spectrum sensing at physical layer and the packet scheduling at MAC layer, over the wireless DSA networks. Under the proposed CREAM-MAC protocol, each secondary user is equipped with a cognitive radio-enabled transceiver and multiple channel sensors. Our cooperative sequential spectrum sensing scheme improves the accuracy of spectrum sensing and further protects the primary users. The proposed CREAM-MAC enables the secondary users to best utilize the unused frequency spectrum while avoiding the collisions among secondary users and between secondary users and primary users. We develop the Markov chain model and M/GY/1 queueing model to rigorously study our proposed CREAM-MAC protocol for both the saturation networks and the non-saturation networks. We also conduct extensive simulations to validate our developed protocol and analytical models.

Over the past few years there has been a growing demand for radio resources and at the same time these resources are under utilized due to static spectrum allocation techniques. Dynamic spectrum access (DSA) has been thought of as a solution that would satisfy both the growing demand for radio resources and to efficiently utilize the spectrum. The radio devices that have the capability to dynamically sense the spectrum and access the under utilized bands are called cognitive radios (CR). There are two broad classes of users in CR, the primary user is a licensed user of a particular radio frequency band and the secondary users are unlicensed users who cognitively operate without causing harmful interference to the primary user. In this paper we consider a denial attack on centralized DSA networks where a malicious secondary user masquerades as a primary user and effectively shuts off access to all other secondary users. Note that this problem is unique to CR due to the distinction between primary and secondary users. We propose a public key cryptography based primary user identification mechanism that prevents malicious secondary users from masquerading as primary users. We show that the proposed identification mechanism and the associated key management are computationally light weight. We also discuss some advantages and limitations of the proposed identification mechanism.

Cognitive radio is an innovative technique for spectrum management which uses Dynamic Spectrum Access (DSA). DSA has the potential to mitigate the spectrum scarcity by letting the Secondary User (SU) access the idle spectrum unused by the Primary User (PU). DSA improves the spectrum efficiency via spectrum sensing and optimal spectrum access. Spectrum sensing should be perfect so that the SU does not cause interference to the PU. Moreover, the channel selected should be the best for maximising throughput of the SU. In this paper we consider a best channel selection problem in Cognitive Radio Networks (CRNs). The problem is modelled as optimal stopping problem where the controller at each state can stop or continue sensing based on the channel gains achieved. There is a Markovian relation given between the channel occupancies of PU. The stopping rule comes out to be simple threshold rule. The controller stops sensing when the channel gain exceeds the given threshold.

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.

Motivated by the low utilization of the licensed spectrum across many frequency bands, sensing-based oppor- tunistic spectrum access has recently emerged as an alternative to the outdated exclusive spectrum access policy. Under this new paradigm, a secondary (unlicensed) user monitors a primary (licensed) frequency band for a given and opportunistically transmits if it does not detect any ongoing licensed operations. Evidently, selection of the parameters involves balanc- ing a tradeoff between the speed and the quality with which the secondary user senses the licensed band. With the average throughput as the performance criterion, we obtain the parameters so as to optimize the performance of the secondary user while providing the primary user with its desired level of interference protection. I. INTRODUCTION As evidenced by recent measurements, many frequency bands across the licensed spectrum are significantly under- utilized (1), (2). This finding suggests that the spectrum scarcity, as perceived today, is largely due to the inefficient fixed frequency allocations rather than the physical shortage of the spectrum and has led the regulatory bodies to consider the opportunistic access to the temporally/spatially unused licensed bands (a.k.a. the white spaces) as a means to improve the efficiency of spectrum usage. In the absence of cooperation or signalling between the primary licensee and the secondary users, spectrum availability for the opportunistic access may be determined by direct spectrum where the secondary user monitors a licensed band for a given sensing time and opportunistically transmits if it does not detect any ongoing licensed operations. This approach is particularly appealing due to its low deployment cost and its compatibility with legacy primary users and is being considered for inclusion in the upcoming IEEE 802.22 standard for opportunistic access to the TV spectrum (3). Due to their ability to autonomously detect and to react to the changes in the spectrum usage, secondary users equipped with the spectrum capability may be considered as a primitive form of the cognitive radio (4). Design of any scheme involves balancing a tradeoff between the quality and the speed of through an appropriate selection of the time. As we shall illustrate, in the context of spectrum sensing, may be fine- tuned to enhance the secondary users' perceived quality-of- service (QoS) as long as the regulatory constraint for the protection of the primary users against harmful interference is satisfied. In particular, we will obtain the optimum times at different stages of the spectrum to maximize the average throughput of the secondary user. In this paper, simple energy detection (a.k.a. radiometry) (5) is chosen as the underlying detection scheme. In general, when some information about the structure of the primary signal is available, ad hoc feature-detectors offer a better performance (6). We note, however, that the methodology employed in this paper may be applied to optimize different spectrum sensors once the quality is characterized in terms of the time. The remainder of this paper is organized as follows. The regulatory constraints on spectrum are described in the following section. Section 3 provides an overview of the energy-based spectrum sensing. The optimum times for different stages of the spectrum are derived in Section 4. Finally, this paper is concluded in Section 5.

In order to maximize the transmission throughput and quality of secondary users (SU) in an opportunistic spectrum access (OSA) systems operating under practical constraints of continuous collisions between the secondary and primary users (PU), we have studied the frame duration behavior and SU's detection frequency under difficult OSA interference and noise conditions. Having analyzed collisions from the SU point of view we first generate a mathematical modeling of the signal to interference and noise rate (SINR) for the SU then, an optimal frame duration is obtained by analyzing characteristics of the SINR in various OSA scenarios. For doing this we have defined the average detection frequency by analyzing the average fading duration of the SINR. This new approach provides a tradeoff between the collision and frequency efficiency as well as improving system's overall performance.

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 Dynamic Spectrum Access (DSA) policy, a secondary user (SU) is allowed to access the primary user (PU) channel when it is idle. This access has to be disruption free for the PU. Literature on DSA focuses on PU and SU signal interferences as the main source of disruption. However the idle state may result from a non-transmitting activity such as the case where the primary user is in the Backoff Window in CSMA/CA networks. This particular idle state can be wrongly seen as an opportunity for SU to access the channel. However, accessing the channel in this context will cause Hidden Collision (HC) and will decrease the primary user performance. In this paper, we extend our previous work on HC and propose to distinguish the PU behaviour, modeled as a three states process, from the channel evolution modeled as an ON/OFF process. To combine these two interdependent processes we use the Hidden Markov Model (HMM) and we propose a solution to predict the PU state and therefore reduce the hidden collision effect. As a proof of concept, our approach accuracy is evaluated using a set of inputs obtained from simulation. We demonstrate the ability of the model to predict accurately enough the PU state and reduce hidden collision.

Cognitive Radio (CR) technique has been proposed for improving spectrum efficiency by dynamic spectrum access. In Cognitive Radio Networks (CRNs), unlicensed Secondary Users (SUs) with CR can utilize licensed spectrum without interfering licensed Primary Users (PUs). For effectively avoiding interference with licensed PUs and malicious attacks from jammers, a two-stage Learning-based Optimal Channel Selection (LOCS) algorithm for unlicensed SUs in distributed heterogeneous CRNs is proposed in this paper. The LOCS algorithm enables SUs to obtain real states of the licensed channels without knowing their information. Hence, SUs using LOCS algorithm can efficiently avoid collision and attack with PUs and jammers. Besides, the LOCS algorithm considers hardware limitation of the SUs, i.e., SUs can only sense and access parts of the license spectrum during any given time. SUs can select the optimal channels for spectrum sensing and data transmission by using the LOCS algorithm. Simulation results show the efficiency of our proposed algorithm in terms of collision and attack avoidance.

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.

In cooperative spectrum sharing networks, dynamic spectrum access is regraded as an important and challenging issue. In this paper, we consider a non-real-payoff cooperative spectrum sharing between one primary user (PU) and one secondary user (SU) over multiple time slots where the channel conditions are changeable due to the channels fading. However, the real-payoff means is that the cooperative spectrum sharing between the PU and the SU is over a time slot where the channel conditions are constant. There exists three access means: the PU's access including the direct and the relay links, and the SU's access. We propose the access decision algorithm considering the access reward and the switching cost for the non-real-payoff means. Herein, the access reward depends on the system's capacity based on the links' channel conditions and the switching cost represents the overheads such as feedbacks and signallings in the communication networks. The access decision problem is formulated as a constrained Markov decision process (CMDP). The objective is to maximize the overall reward with the access cost constraints including the users' energy constraints and the PU's quality of service (QoS) constraints. The value iteration and Q-learning algorithms are used to determine the optimal access policy.

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.

In order to mitigate the problem of crowded radio spectrum, dynamic spectrum access (DSA) has become the solution and a research focal point. The number of works in wideband spectrum sensing is dramatically increasing recently due to its importance in cognitive radio (CR) networks. Most works assume that secondary users (SUs) are synchronous with the primary users' (PUs) network. However, in many practical systems the SUs will have no information about the PUs' communication protocols. Furthermore, it is also possible that communications among PUs are not based on synchronous operation. In order to address such problems, a contention-based wideband DSA algorithm with asynchronous cooperative spectrum sensing (CSS), called the DySac, is proposed. In this scheme, the SUs need not maintain synchronism with the PUs, and the SUs who intend to access the primary network compete among each other for available channels. Performance analysis and simulations are conducted to evaluate the proposed DySac.