Relay selection and residual self-interference mitigation for cognitive full-duplex two-way MIMO relaying system

In this report, we point out on a system in which secondary user (SU) transmitter communicates with a SU receiver via a secondary relay (SR) under the interference from multiple primary users (PUs). Power allocated to SU transmitter on the basis of two constraints of PU, viz., outage threshold and outage transmission rate. In this case, performance of PU does not degrade due to these tolerable constraints. Direct link does not occur between the SU transmitter and receiver because of shadowing. A SR used to link the SU transmitter to SU receiver that is based on decode-and-forward (DF) scheme. Outage probability (OP) calculated by considering the interferences from all PUs at SR and secondary receiver. We see that the performance of SU network does not always degrade after the consideration of interferences from all PUs and thus, SU transmitter reliably communicates with its receiver under the specific range of primary transmit power of PUs in this system model. Results of this model are verified by the MATLAB simulation.

In cognitive radio networks (CRNs), the secondary users (SUs) need to continuously detect whether the primary users (PUs) occupy the spectrum. In order to improve the spectrum sensing accuracy, a novel reliable cooperative spectrum sensing strategy based on the detection results relayed twice from the secondary relays (SRs) to the secondary source (SS), referred to as CSS-DRT, is proposed in this paper. In this scheme, the spectrum sensing slot is divided into four equal sub-slots. In the first and third sub-slots, the SS and SRs detect the PU by themselves. Then, in the second sub-slot, if the SRs that detect the PU during the first sub-slot are more than or equal to a prespecified quantity, the corresponding SRs will send their flag signals (FSs) to the SS while the others keep quiet, where the FS is narrowband and indicates that the PU is present. Otherwise, if the SRs that detect the PU during the first sub-slot are less than the prespecified quantity, all the SRs will keep quiet in the second sub-slot. Meanwhile, the SS detects the PU based on the received signals from the PU and SRs. And, the SS uses the same method as employed in the second sub-slot to detect the PU in the last sub-slot wherein the SRs send their FSs based on their detections made during the third sub-slot. Finally, an ultimate decision is made by the OR ruler based on the SS detection results obtained during the spectrum sensing slot. Besides, we derive the closed-form expressions of the false alarm and detection probabilities for the proposed CSS-DRT scheme. In the end, simulation and numerical results show that our proposed scheme can achieve better performance than the non-cooperative method and an existing cooperative spectrum sensing method.

In this paper, we propose a cooperative spectrum sharing protocol for cognitive radio networks (CRNs) which operate in underlay mode with an automatic repeat-request (ARQ)-based primary user (PU) including primary transmitter (PT) and primary receiver (PR) and a bidirectionally communicating secondary user (SU) which consists of the nodes S1 and S2. In ARQ-based PU, ACKnowledgement/Negative-ACKnowledgement (ACK/NACK) messages are sent from PR to PT and listened by S1 and S2 to control the PU's packet success. Si (i=1 or 2) alerts both PT and PR if its reception from PT is successed or failed and PR considers the link from Si or PT, respectively. PU transmits its packet by accessing the spectrum alone or by cooperating with SU or under an interference caused by SU. If PT transmits alone its packet successfully, in the next time slot it transmits a new packet in underlay mode during which SU access the spectrum simultaneously with a tolerable interference level to improves the PU's performance. Conversely, if PT fails to transmit alone its packet and at least one of the nodes S1 and S2 success to decode it, then S1 or S2 cooperates with PT attending as a relay to enhance the PU's throughput in the next time slot during which PT stays silent. If both of S1 and S2 fail to decode PT's packet, PT retransmits its packet in underlay mode. When the first transmission of PT's packet is failed in underlay mode, PT retransmits this packet alone. We derive analytical expressions for the throughputs of PU and SU and show that the proposed protocol significantly improves the PU's throughput compared to non-CR scheme while stabilizing the SU's throughput at high SNR values.

In this paper, we consider a cognitive multi-hop relay secondary user (SU)\nsystem sharing the spectrum with some primary users (PU). The transmit power as\nwell as the hop selection of the cognitive relays can be dynamically adapted\naccording to the local (and causal) knowledge of the instantaneous channel\nstate information (CSI) in the multi-hop SU system. We shall determine a low\ncomplexity, decentralized algorithm to maximize the average end-to-end\nthroughput of the SU system with dynamic spatial reuse. The problem is\nchallenging due to the decentralized requirement as well as the causality\nconstraint on the knowledge of CSI. Furthermore, the problem belongs to the\nclass of stochastic Network Utility Maximization (NUM) problems which is quite\nchallenging. We exploit the time-scale difference between the PU activity and\nthe CSI fluctuations and decompose the problem into a master problem and\nsubproblems. We derive an asymptotically optimal low complexity solution using\ndivide-and-conquer and illustrate that significant performance gain can be\nobtained through dynamic hop selection and power control. The worst case\ncomplexity and memory requirement of the proposed algorithm is O(M^2) and\nO(M^3) respectively, where $M$ is the number of SUs.\n

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.

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.

In this paper, we propose to optimize the power of Primary User (PU) and secondary relays R k to maximize the Detection Probability (DP). We suggest to maximize the detection probability of cooperative spectrum sensing with relay selection. One relay is chosen to amplify the PU signal to the fusion center D where spectrum sensing using the Energy Detector (ED) is performed. The selected relay offers the highest instantaneous Signal to Noise Ratio (SNR) and allows to increase the DP since the best relay is selected. Optimal power allocation allows 0.7 dB gain with respect to Uniform Power Allocation where the same power is allocated to PU and selected relay. The proposed optimal power allocation is applied for opportunistic Amplify and Forward (AF) relaying, Partial and Reactive Relay Selection (PRS and RRS).

We propose continuous power allocation strategies for secondary users (SUs) based on sensing the primary user (PU) channels in a multiband cognitive radio (CR) network. Unlike the conventional sensing-based spectrum sharing, where there are two transmit power levels corresponding to whether the PU is sensed present or not, in the proposed strategy, the power levels are continuous functions of the sensing statistics, and optimized with respect to the achievable rate of the SU. The continuous power allocation function is parameterized by some channel parameters of the PU and SU, and we treat the cases of perfect and quantized channel state information (CSI) separately, where the former provides an upper bound on the achievable rate with full channel information; and the latter constitutes an efficient practical power allocation method for the SU with statistic/partial channel information. The power control process consists of two phases: in the first phase, the SU listens to the multiple bands licensed to the PU and obtains the sensing statistics, e.g., the received signal energies on these bands; in the second phase, the SU adjusts its transmit power levels on these bands based on the sensing results. Optimal power allocation schemes are derived to maximize the achievable rate at the SU under several possible combinations of the peak/average transmit power constraints at the SU and the peak/average interference power constraints at the PU. Simulation results demonstrate that the proposed strategies can significantly improve the achievable throughput of the SU compared to the conventional methods.

Slotted Aloha and carrier sensing multiple access (CSMA) are effective random access protocols, which can also be important elements of more advanced media access protocols. In this paper, we investigate slotted Aloha and CSMA protocols in a cognitive radio network, where primary users have higher priority than secondary users and secondary users need to monitor the channel to avoid interference to the primary users, it is thus proposed that slotted Aloha is used for primary users to access the channel and secondary users use slotted CSMA to sense the time slots of slotted Aloha and transmit their packets during idle time slots. A Rayleigh fading channel is considered and we derive the throughput of slotted Aloha and CSMA for the primary and secondary users.

We assume a set of cognitive relay nodes that assists both primary and secondary transmissions in a time-slotted cognitive radio networks. To regulate the channel access of the various nodes in the network, we propose an overlapped spectrum sensing strategy for channel sensing, where the secondary source node senses the channel from the beginning of the time slot and the cognitive relay nodes sense the channel for double the sensing time used by the secondary source node to detect the activities of both the primary and secondary source nodes. Hence, the secondary source node has an intrinsic priority over the relay nodes. The relay nodes help both the primary user and the secondary user to deliver their unsuccessfully decoded packets at their destinations. In a given time slot, the scheduled relay node for data transmission starts its transmission when both the primary and secondary users are sensed to be inactive (i.e. have no data to transmit). We propose two optimization-based formulations with quality-of-service (QoS) constraints involving average queueing delay and average service rate requirements.We investigate both cases of perfect and imperfect spectrum sensing. To further enhance the usersʼ QoS requirements, we propose three packet decoding strategies at the relay nodes and compare their performance. We derive an upper bound on the secondary queue average service rate to determine which decoding strategy can achieve that bound. Our numerical results show the benefits of relaying and its ability to enhance the performance of both the primary and secondary users. Moreover, the performance of the proposed schemes is close to the derived upper bound.

In this paper, the spectrum leasing in Cognitive Radio Networks (CRN) based on property-right model is addressed when a single Primary User (PU) coexists with multiple Secondary Users (SU). In this model, the PU as the spectrum owner allows the SU to use a portion of the spectrum band in exchange for providing cooperative relaying service. We propose a novel game theoretic model, where the PU is able to monitor the behavior of the SUs in terms of cooperation. Using the proposed credit-based mechanism, the PU will be notified about any dishonest action of the SUs after they utilized the spectrum access, therefore the PU may decide not to select the fraudulent SUs in the next time slots. The proposed accumulative cooperative credit keeps the record of the portion of power is used by each SU to perform the relaying service. In each round, the PU observes the SUs' credit and selects a reliable one with a relatively good channel condition.

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.

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.

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 Cognitive Radio Networks (CRNs), Primary Users (PUs) can share their idle spectra with Secondary Users (SUs) under certain mechanisms. In this paper, we propose a distributed-centralized and incentive-aware spectrum sharing scheme for the multiple-PU scenario, which introduces a Random Leader who is elected randomly from SUs or PUs. The distributed aspect of our scheme lies in that it requires no central control entities, which can be independently implemented within a distributed spectrum market. The centralized aspect is that the leader draws up and assigns the socially optimal contracts for all PUs and SUs in a centralized manner, which maximizes the throughput of the whole network and attains the economic robustness (including Incentive Compatibility and Individual Rationality). Analysis shows that the proposed scheme takes in the advantages of both centralized and distributed schemes but overcomes their weaknesses. We use the proposed scheme to study two sharing scenarios: the short-term and the long-term spectrum sharing. The Short-Term Sharing (STS) focuses on distributing PUs' idle spectra within one time slot while the Long-Term Sharing (LTS) considers multiple slots, where the spectrum mobility must be investigated. As an integrated design of both STS and LTS, our scheme not only fulfils SUs' heterogeneous spectrum requirements but also obtains the socially optimal throughput while accounting for both SUs' and PUs' incentives.