Bayesian Potential Games to Model Cooperation for Cognitive Radios with Incomplete Information

This paper addresses first the problem of max-min fair (MMF) link transmissions in wireless sensor networks (WSNs) and in a second stage studies the joint link scheduling and transmission power assignment problem. Given a set of concurrently transmitting links, the MMF link transmission problem looks for transmission powers of nodes such that the signal-to-interference and noise ratio (SINR) values of active links satisfy max-min fairness property. By guaranteeing a “fair” transmission medium (in terms of SINR), other network requirements may be directly affected, such as the schedule length, the throughput (number of concurrent links in a time slot), and energy savings. Hence, the whole problem seeks to find a feasible schedule and a power assignment scheme such that the schedule length is minimized and the concurrent transmissions have a fair quality in terms of SINR. The focus of this study falls on the transmission power control strategy, which ensures that every node that is transmitting in the network chooses a transmission power that will minimally affect the other concurrent transmissions and, even more, achieves MMF SINR values of concurrent link transmissions. We show that this strategy may have an impact on reducing the network time schedule.

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.

Empowered by the cognitive radio technology and motivated by the sporadic channel utilization, both spatially and temporally, dynamic spectrum access networks, also referred to as cognitive radio networks, have emerged as a solution to improve spectrum utilization and provide more flexibility to wireless communication. In this paper, we study the channel allocation problem in wireless cognitive mesh networks. For the allocation to be feasible, served mesh clients must establish connectivity with a backbone network in both the upstream and the downstream directions, and must have the SINR (signal-to-interference and noise-ratio) of the uplink and the downlink with their parent mesh routers within a predetermined threshold. We propose a receiver-based channel allocation strategy and show that this strategy outperforms other strategies in terms of the number of mesh clients served, and the fact that no common control channel is needed for coordinating the communication process. Furthermore, we formulate the receiver-based channel allocation problem in wireless cognitive mesh network as a mixed integer linear program (MILP) and propose a heuristic solution.

We investigate energy efficient resource allocation in a downlink energy harvesting cognitive radio (CR) network, where multiple secondary users (SUs) with energy harvesting capability are assumed to share multiple channels with the primary user (PU) under the transmit power constraint and the interference power constraint. Specifically, one channel is assumed to be allocated to only one SU for information transmission and the rest SUs can do energy harvesting on the channel. The problem of joint channel and power allocation to maximize the energy efficiency of the CR network is investigated, and an efficient iterative algorithm based on Dinkelbach method and convex optimization is proposed. It is shown that the proposed algorithm significantly improves the energy efficiency of the CR network compared to reference algorithms.

One of the ways to harness the radio bands that are not used by their primary owners, is to allow opportunistic use of the bands to be used by secondary users such that they do not interfere with the primary users. Most often, multiple secondary users contend to acquire the bands that are available. Proper scheduling techniques can resolve such contentions. However, all scheduling techniques have their own pros and cons. In this paper, we propose scheduling algorithms for dynamic spectrum access (DSA) networks that allocate channels by exploiting favorable instantaneous channel conditions of secondary users and the transmission activities of primary users. We propose two scheduling algorithms- the first one focuses on maximizing the throughput and the second one focuses on social welfare. Scheduling is performed at the beginning of each super-frame where appropriate slots(s) are assigned to secondary users. In order to better utilize the channels, multiple secondary users are allocated the same channel in the same time slot as long as there is no interference between them. However, finding such conflict-free independent set of secondary users is a NP-complete problem. We use the signal to interference and noise ratio (SINR) to find the independent sets for throughput maximization, while we use the allocation history for the achieving fairness. Using simulation, we show the performances of the proposed algorithms in terms of throughput, number of slots allocated, and fairness achieved among the users.

Opportunistic spectrum access in cognitive radio networks is regarded as solution to spectrum scarcity caused by the static allocation of the frequency spectrum. Unlicensed secondary users (SUs) access the spectrum opportunities which are licensed not licensed to them opportunistically without creating harmful interference to the licensed primary users (PUs). In typical wireless communications, to negotiate and establish a link between transmitter and receiver, common control channel is used. However, attackers can identify the common channel and jam it or overhear and misuse the information. In this paper, we present rendezvous processes for dynamic spectrum access in cognitive wireless networks where transmitter and receiver pair meets in a common channel in an ad hoc manner and establish a link for their communications. Rendezvous processes for dynamic spectrum access provides robust link that prevents any security attacks such as jamming, denial-of-service attack, etc. This paper provides comparison of different rendezvous processes and their applicability in cognitive wireless ad hoc networks.

TV white spaces (TVWS) can be used by secondary users as long as they do not cause harmful interference to primary users (PUs). Regulatory authorities worldwide have mandated the use of geo-location database (GLDB) for protection of incumbent users. In a wireless TVWS network, interference could be due to either co-channel interference or adjacent channel interference. Recent studies have shown that aggregate adjacent channel interference from a high density of mobile users using low power in multiple adjacent channels is as harmful as co-channel interference even if each single adjacent channel interference stays below the GLDB D/U (desired to undesired) ratio constraint. When there is a high density secondary users (SUs) in a TVWS network, there will high interference among SUs and a possibility of harmful interference to primary users (PUs). Power control is therefore necessary to protect PUs against harmful interference and to reduce the level of interference among SUs. In this paper we propose a firefly algorithm based power control algorithm for a GLDB based wireless TVWS network that take into consideration interference constraints at the primary user (PU) and SU. The algorithm also takes into consideration both co-channel and adjacent channel interference. Simulation results show that the proposed algorithm protects TV receivers against harmful interference and results in an improvement of signal to interference and noise ratio (SINR) for SUs.

We propose a coordinated non-sensing medium access control (MAC) protocol in dynamic spectrum access networks namely distributed coordinated dynamic spectrum reservation (DCDSR) protocol which is not based on the cognitive radio technology. All primary users (PUs) and secondary users (SUs) have two transceivers operating in common control channel and licensed data channels to access control and data packets in the corresponding control and data frames, respectively. PUs will inform SUs which channels will be used in next data frame and then SUs reserve unused channels by contending with each other during contention interval (CI) in control frame. The available channels which can be reserved by SUs will depend on the channel usage of PUs and further affect the throughput of SUs. Whenever SU successfully reserve channel in CI, they will start access reserved channel in next data frame after the end of CI. This will cause the wasted idle time for those SUs which have successfully reserved channel whenever the CI doesn't finish. SU which couldn't successfully reserve channel in current control frame should try to reserve again in next control frame. Thus, the duration of CI will affect the delay and wasted idle time of SUs. We analyze and simulate the performance of throughput, delay and wasted idle time in DCDSR. The analytical and simulation results show that the proposed DCDSR performs very well.

In cognitive radio, the throughput efficiency of the secondary user (SU) is determined by spectrum sensing performance and the secondary user's available power to send data. Because the secondary user expends energy for spectrum detection and to maintain cooperation among numerous SUs, transmission power can be reduced. To compensate for this energy, cognitive radio has devised an energy harvesting technology in which the SU may harvest energy from the primary (PU) signal and use it to broadcast data and extend the lifetime. In a typical Energy Harvesting Cognitive Radio Network (EHCRN), SU can perform sensing and harvesting in different slots, reducing the secondary user's transmission time and lowering throughput. In a cooperative wireless network with energy detecting spectrum sensing, the RF energy harvesting approach is researched, and various optimization studies are investigated in this work. First, an energy harvesting is considered with the power splitting technique, Power Splitting Energy Harvesting Cognitive Radio Network (PSEHCRN) to measure the residual energy of SU that can be utilize to improve the transmission efficiency of SU and obtained expressions for throughput and lifetime. Further an energy harvesting with adaptive time switching mode of operation namely Adaptive Time Switching Energy Harvesting CRN (ATSEHCRN) has proposed and analyses the performance in terms of harvested energy, transmission power, throughput and lifetime of SU. This research also offers the Optimum Energy Harvesting Cognitive Radio Network (OTEHCRN)., an optimum energy harvesting technique that can perform spectrum sensing and energy harvesting simultaneously, with the entire incoming radio frequency (RF) power being utilised for energy harvesting. Reduced energy consumption paired with higher energy harvesting allows more energy to be accessible for transmission, resulting in increased SU throughput and longevity. Harvested energy, transmission power, throughput and lifetime are analysed with half duplex and full duplex mode of energy harvesting and compared with the different energy harvesting schemes. The cognitive radio performance of all studies has been verified with MATLAB simulation results.

In this paper we address the control channel assignment problem in a cognitive radio based wireless network, namely the CogMesh. Such a network is featured by the dynamic spectrum sharing of the secondary users coexisting with the primary users. The opportunistic nature of the spectrum utilization among the secondary users makes a global control channel infeasible. The self-coordination of the network, hence, becomes a challenge task. Considering the fact that common channels may temporarily exist among a local group of secondary users, we propose an adaptive approach that selects local common control channels independently by each secondary user according to the qualities of the detected spectrum holes and the choices of its neighbors. To achieve this, a swarm intelligence-based algorithm is used to facilitate the common control channel selection. The idea is to use HELLO messages periodically broadcasted by neighbors as the pheromone to rank the common channels so as to expedite the channel selection process. The algorithm is completely distributed and therefore scalable. Moreover, it is simple, flexible, adaptive, and well balanced on the exploitation and exploration of the radio resources. The behaviors and performance of the proposed algorithm are verified by simulation.

Cognitive radio (CR) technology allows secondary users (SUs) to share primary user's (PU's) spectrum band by adapting its transmission power in a sensing-based spectrum sharing manner. Spectrum sensing is an important activity in the CR network. Spectrum sensing is used to detect availability of a channel in the PU's spectrum band for the SUs. Presence of attackers such as primary user emulation (PUE) attackers in CR networks imposes some security threats to the SUs which affects the spectrum sensing decisions. In PUE attack, SUs are mislead from using the PU's spectrum band which results in degradation of SU's throughput. To enhance SU's throughput, we have considered hybrid spectrum access scheme with spectrum prediction in this paper. In hybrid spectrum access scheme, the SU switches between overlay or underlay modes based on spectrum sensing decision available at SU. In predictive scheme, the SUs will sense only those channels which are predicted to be idle. Simulation results show that degradation in SU's throughput due to presence of PUE attackers can be compensated by using spectrum prediction in conjunction with hybrid spectrum access.

The use of sharing channel simultaneously has become the trend in telecommunication technology particularly in network with distributed users as the allocation of frequency spectrum becomes more crowded. The proposed power control method in cognitive femtocell network is based on game theory (commonly known as power control game, PCG). This method uses utility function formula as the goal of game theory for power strategy in power update process. Utility function formula of Proposed PCG includes channel sharing factor that aimed to accommodate the system requirement of channel sharing. The result showed that the implementation of channel factor is inversely proportional to the signal to noise and interference ratio (SINR) and transmit power, but proportional to utility function. In comparison of user transmit power and SINR with two other methods, can also be conclude that Proposed PCG was able to achieve SINR of 5.49 dB and above the SINR target 5 dB, while the Thalabani (TB) and Koskie-Gajic (KG) were only able to achieve respective SINR of 4.87 dB and 4.98 dB. It can be concluded that the Proposed PCG was better in achieving the SINR target. It means that the quality of service in this system can be fulfilled properly.

Asynchronous channel hopping (ACH) systems are widely used for the blind rendezvous among secondary users in cognitive radio networks without requirement for global synchronization and common control channels. We can view an ACH system with n channels as a set of sequences of a common period t on an alphabet of size n satisfying certain rotation closure properties. For any two distinct sequences u, v in an ACH system $\mathcal {S}$ , every l ∈{0,1,⋯ , t − 1} and any letter j in the alphabet, if there always exists i such that the i-th entries of u and Ll(v) are identical to j where Ll(v) denotes the cyclic shift of v by l, then we say that $\mathcal {S}$ is a complete ACH system. Such a system can guarantee rendezvous between any two secondary users who share at least one common channel. It is well known that $t\geqslant n^{2}$ . When the equality holds, $\mathcal {S}$ is called a perfect ACH system. By applying characters of cyclic groups, we obtain a new upper bound on the number of sequences in a perfect ACH system. Furthermore, when q is a prime power and n = q − 1, we present a construction of homogeneous complete ACH systems of period t = 2n2 + o(n2).

This paper focuses on spectrum handoffs in a cognitive radio network where secondary (unlisenced) users (i.e. cognitive radios) opportunistically use frequency channels as long as the aggregate interference caused at the primary (licensed) users does not exceed a certain threshold. When harmful interference is caused to a primary user, or when the quality of service perceived by a secondary user is not satisfactory, the secondary user has to initiate a spectrum handoff to quickly vacate the channel it is occupying. The proposal in this paper is a fuzzy-based approach able to make effective spectrum handoff decisions in a context characterized by uncertain, incomplete and heterogeneous information.

When the channel measurement update rate is very slow compared to the channel fluctuations, the performance of conventional power control algorithms is greatly reduced. In this paper we introduce novel method to update the transmit power in such extreme situations. We propose to use random power allocation with certain distribution function and then using the channel measurements to update the statistics of this random power rather the power value itself. The truncated inverted exponential distribution is one candidate for the power distribution which is used in this paper. This distribution has one parameter which can be easily updated according to the channel quality. The signal-to-interference and noise ratio (SINR) is used as an indicator for the channel quality. The probability of outage when using the proposed power allocation is also given in mathematical form. Simulations show that, one may improve the average SINR when using the proposed algorithm compared to the conventional distributed power control algorithm.