Non-orthogonal multiple access protocol for overlay cognitive radio networks using spatial modulation and antenna selection

In this paper, we consider a cooperative cognitive radio relay network (CCRRN), in which there is a pair of primary transmitter (PT) and primary receiver (PR) with each having a single antenna, a secondary transmitter (ST) equipped with two antennas and a secondary receiver (SR) having a single antenna. We assume that ST operates in a half-duplex mode with an amplify-and-forward (AF) cooperative transmission scheme adopted. For such a system, a novel transmission scheme for CCRRN based on uniquely-factorable constellation pair (UFCP) is proposed, which enables ST to transmit its own information to SR without knowing its channel links to PR and SR while assisting PT transmission. It is shown that one of significant advantages of our proposed new scheme is that in a noise-free case, PR and SR are able to decode their own signals uniquely and that in a Gaussian noise case, they are still able to reliably decode their own signals with full diversity. In addition, a tight upper bound of average pairwise error probability (PEP) for the maximum likelihood (ML) detector is derived, showing that full diversity is achieved. With this, an optimal power allocation strategy is proposed that minimizes the worst-case upper bound.

This paper illustrates the performance of bit error rate based selection combining (BER-SC) protocol for adaptive cooperative cognitive radios. In the proposed framework, the unlicensed (i.e. secondary) system utilizes an adaptive mode of transmission to help the licensed (i.e. primary) system to achieve the desired quality of service in exchange for opportunistic spectrum access. The total transmission is divided in two phases. In Phase I, the primary transmitter (PT) broadcasts the data to the primary receiver (PR), which is overheard by the secondary transmitter (ST) and secondary receiver (SR). In Phase II, ST decodes the primary data and linearly combines its own data with the primary data. Using M-QAM the combined data is adaptively modulated, where M = 4, 16 or 64 depending on the received channel feedback, and relayed to PR and SR. At PR, BER-SC is employed to retrieve the primary data, and at SR interference cancellation is used to retrieve the secondary data. The analytical expressions are derived for the BER and the outage probability. The obtained results demonstrate the higher performance gains for both primary and secondary system by using adaptive mode of transmission at ST and BER-SC at PR.

In this paper, the problem of security in multiple input multiple output (MIMO) system has been analysed in the presence of an eavesdropper in cognitive radio networks. Multiple primary and secondary users communicate with the primary and secondary receiver, respectively. The secrecy capacity at primary receiver (PR) and secondary receiver (SR) have been calculated. At first, we use zero-forcing (ZF) precoding at the relay which enhances the secrecy capacity of PR and SR by nullifying the impact of interference. Secondly, we use a scheme to improve the secrecy capacity of the PR and SR using the existing interference energy of the communication medium employing selective precoding (SP) at the relay. Finally, we employ phase alignment precoding (PAP) for further increase in the secrecy capacity for PR and SR by using the destructive part of interference. Our analysis shows that among the three precoding techniques, the best performance is achieved by using the PAP at the relay in terms of secrecy capacity, complementary cumulative distribution function (CCDF) and outage probability analysis.

It has been widely accepted that cognitive radio can substantially improve the spectrum utilization compared with traditional spectrum allocation strategies. Cognitive radio technology enables secondary users to coexist with primary users opportunistically or concurrently. In the latter scenario, the primary user allows the secondary user to access its licensed spectrum, as long as the quality of service (QoS) of the primary transmission is guaranteed. Beamforming is a practical way to achieve this goal by utilizing multiple antennas to limit the interference at the primary receiver (PR) to a tolerable level. With transmit beamforming and receive beamforming, a multi-antenna secondary transmitter (ST) with the knowledge of cross channel state information (CSI) can project signals to appropriate directions such that no harmful interference is received at PR, while the secondary receiver (SR) can separate and recover the intended signals reliably. Perfect or imperfect knowledge of cross CSI at ST results in different interference conditions as well as different transmit strategies. The interference received at PR in the perfect cross CSI case is controllable, and hence ST can precisely determine the transmit beamforming directions to gain the maximum benefit under the primary interference constraint. However, such a strategy is not always suitable in the imperfect cross CSI case, due to the uncertainty of CSI error directions and amplitudes. In this case, ST needs to ensure that the interference constraint would not be violated even with the worst CSI error. In this thesis, we first study cognitive beamforming subject to the secondary power constraint and the primary interference power constraint. With bounded error model for the cross CSI, we rewrite the error boundary expressions as a set of linear matrix equalities, and then convert the whole problem into a convex optimization problem to calculate the optimal solution. When no cross CSI is available at ST, we aim at maximizing the secondary sum throughput subject to the interference expectation constraint and interference outage probability constraint at PR, respectively. We prove that under the former constraint, the beamforming problem can be formulated as a conventional MIMO transmission problem, which can be easily solved via the water-filling method. Under the latter constraint, we find that the interference power is related to the eigenvalues of the covariance matrix of the secondary signals, and thus it can be expressed as a linear combination of multiple chi-square distributed variables. By exploiting the impact of the eigenvalues on the interference outage probability and establishing the relationship between the vibrations of secondary covariance matrix and its eigenvalues, we design an algorithm for this beamforming problem. In the second part of this thesis, we focus on beamforming in a multi-antenna cognitive radio system with transmission of multiple secondary data streams subject to the individual signal-to-noise ratio constraint per secondary data stream and the primary interference power constraint. The objective is to minimize the secondary transmit power consumption. Both perfect and imperfect cross CSI cases are considered and in both cases, the beamforming feasibility is tested. By exploiting the individual SNR constraints, we formulate the cognitive beamforming problem as an optimization problem on the Stiefel manifold. For zero forcing beamforming, we derive a closed form beamforming solution. For nonzero forcing beamforming, we prove that the strong duality holds for the nonconvex primal problem and thus the optimal solution can be easily obtained by solving the dual problem. In the case of imperfect cross CSI, we apply the S-procedure method to reformulate the problem and provide an algorithm to obtain the beamforming solution. Finally, we raise some interesting open problems for the future work.

We consider in this paper, a spectrum sharing cognitive radio system with a ratio selection scheme; where one out of N independent-and-identically-distributed transmit antennas is selected such that the ratio of the secondary transmitter (ST) to the secondary receiver (SR) channel gain to the interference from the ST to the primary receiver (PR) channel gain is maximized. Although previous works considered perfect, outdated, or partial channel state information at the transmitter, we stress that using such assumptions may lead to a feedback overhead for updating the SR with the ST-PR interference channel estimation. Considering only statistical knowledge of the ST-PR channel gain, we investigate a ratio selection scheme using a mean value (MV)-based power allocation strategy referred to as MV-based scheme. We first provide the exact statistics in terms of probability density function and cumulative distribution function of the secondary channel gain as well as of the interference channel gain. Furthermore, we derive exact cumulative density function of the received signal-to-noise ratio at the SR where the ST uses a power allocation based on instantaneous perfect channel state information (CSI) referred to as CSI-based scheme. These statistics are then used to derive exact closed form expressions of the outage probability, symbol error rate, and ergodic capacity of the secondary system when the interference channel from the primary transmitter (PT) to the SR is ignored. Furthermore, an asymptotical analysis is also carried out for the MV-based scheme as well as for the CSI-based scheme to derive the generalized diversity gain for each. Subsequently, we address the performance analysis based on exact statistics of the combined signal-to-interference-plus-noise ratio at the SR of the more challenging case; when the PT-SR interference channel is considered. Numerical results in a Rayleigh fading environment manifest that the MV-based scheme outperforms the CSI-based scheme provided that a low interference power constraint is deployed, implying that the MV-based scheme is more suitable for practical systems.

This correspondence considers a hybrid cognitive radio (H-CR) where the primary transmitter (PT) transmits message to the primary receiver (PR) whenever traffic occurs by allowing interference level <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</i> from the secondary transmitter (ST) to the PR, and the ST transmits messages to the secondary receiver (SR) by controlling the transmitting power based on spectrum sensing and interference level <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</i> . The ST opportunistically adopts maximum power when it detects that the PT is not transmitting and controls the transmitting power to restrict the interference level from the ST to the PR below <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</i> when alerted that the PT is transmitting. The closed-form expressions of the average rates for the H-CR are derived. Based on the analytical results, the detection probability α and interference level <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</i> are optimized to maximize the average rate of the ST by guaranteeing the average rate of the PT. Analysis and simulation results demonstrate that the former matches well to the latter and the average rate for the ST of the H-CR is better than that of two existing CRs where the ST transmits messages to the SR with maximum power only when the ST recognizes that the PT is not transmitting or with controlled power to limit an interference level from the ST to the PR below a constant irrespective of the PT's activity.

Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) enhance the flexibility and performance of RIS by extending traditional <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$180^{\circ}$</tex-math></inline-formula> half-space coverage to a full <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$360^{\circ}$</tex-math></inline-formula>. Motivated by this, we explore a STAR-RIS-assisted overlay cognitive satellite-terrestrial network (OCSTN) with multiple users. In this setup, a primary satellite source communicates with terrestrial primary receivers (PRs) using the non-orthogonal multiple access (NOMA) scheme, while a decode-and-forward-based secondary transmitter (ST) facilitates primary communications in exchange for spectrum access. A STAR-RIS further aids the ST by simultaneously transmitting and reflecting superposed signals to enhance both primary and secondary communications. The analysis incorporates practical considerations, including imperfect successive interference cancellation (ipSIC) in the NOMA and overlay system, as well as quantization errors introduced by the discrete phase shifts of STAR-RIS elements. For terrestrial Nakagami-<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> fading and satellite shadowed-Rician fading, we derive exact and asymptotic outage probability expressions and ergodic rate bounds for primary and secondary networks. The numerical and simulation results demonstrate that the STAR-RIS-assisted OCSTN consistently achieves superior performance compared to standalone OCSTN benchmarks across key performance metrics.

The authors study robust beamforming and power allocation in cognitive relay networks using several relays in the secondary link. The channel state information is imperfect modelled by Gaussian random variables. First, minimisation of the total transmit power of relays and the secondary transmitter is considered with a constraint on the interference in the primary receiver. Also, a constraint is assumed on the received signal-to-interference plus noise ratio (SINR) in the secondary receiver. In the other scenario, maximisation of the SINR in the secondary receiver is investigated with a limit on the maximum transmit power of relays and the secondary transmitter. For each non-convex optimisation problem, an iterative and robust algorithm is derived. It is proved that the first proposed algorithm converges to the global optimum. Simulation results similarly show the convergence of both algorithms with a few number of iterations. The outperformance of the robust algorithms is shown compared with a non-robust design.

In this paper, we propose a new multi-antennas hierarchical cognitive radio, in which a primary system (PS) not only shares the spectrum resources with a secondary system (SS), but also harvests energy from the SS, achieving a new simultaneous wireless information and power transfer paradigm. Specifically, the secondary transmitter (ST) can help relay PS’s signals via an amplify-and-forward protocol, and a power splitting energy harvesting device is additionally adopted at the primary receiver (PR). A cooperative strategy is proposed for maximizing the achievable rate of the SS while ensuring PS’s achievable rate and PR’s harvested energy, by jointly optimizing a precoder at the primary transmitter, two precoders at the ST (for the PS and SS, respectively), an equalizer at the secondary receiver, and a power splitting factor for the PR. Since the optimization problem is complicated and non-convex, we propose an alternating optimization approach to decompose the original problem into three subproblems, which can finally be formulated as semi-definite programming, difference of convex, and generalized eigenvalue problems. The closed-form solutions are, then, tractably derived. The numerical results are carried out to demonstrate the effectiveness of the proposed design.

The performance of an underlay cognitive radio (CR) system, which can transmit when the primary is on, is curtailed by tight constraints on the interference it can cause to the primary receiver. Transmit antenna selection (AS) improves the performance of underlay CR by exploiting spatial diversity but with less hardware. However, the selected antenna and its transmit power now both depend on the channel gains to the secondary and primary receivers. We develop a novel Chernoff-bound based optimal AS and power adaptation (CBBOASPA) policy that minimizes an upper bound on the symbol error probability (SEP) at the secondary receiver, subject to constraints on the average transmit power and the average interference to the primary. The optimal antenna and its power are presented in an insightful closed form in terms of the channel gains. We then analyze the SEP of CBBOASPA. Extensive benchmarking shows that the SEP of CBBOASPA for both MPSK and MQAM is one to two orders of magnitude lower than several ad hoc AS policies and even optimal AS with on-off power control.

Energy harvesting (EH), which refers to replenishing energy from the environment, is demonstrated to be a promising approach in reducing the operational expenses (OPEX) and increasing the network lifetime of emerging wireless communication technologies by eliminating the need for frequent battery replacing or recharging of wireless devices. Among various ambient energy sources, the focus of this dissertation is on wireless power transfer (WPT) considering the unique characteristic of radio frequency (RF) signals; that is, they inherently carry both information and energy. A particularly interesting scenario arises when sources support simultaneous wireless information and power transfer (SWIPT) to provide a remote, controllable, and on-demand energy source. In this context, one of the promising deployment approaches is SWIPT-enabled cognitive radio networks (CRNs), which offer significant gains in terms of spectral and energy efficiencies. One of the practical scenarios of RF-powered CRN is deploying a number of distributed cognitive sensor nodes, equipped with RF EH modules, to sense a specific area and send the sensed data to an access point while coexisting with a primary licensed network. However, exploiting the full potentials of SWIPT-enabled CRNs is subject to carefully aligning the requirements of the EH unlicensed secondary receivers (SRs) with those of the legitimate primary receivers (PRs). In light of this, the first contribution of this thesis focuses on investigating the problem of beamforming for the downlink of multi-user multiple-input single-output (MU-MISO) CRNs. With the objective of minimising the transmission power of the secondary base station (SBS), optimal and suboptimal solutions for the formulated optimisation problem are provided by jointly optimising the transmit beamforming vector at the SBS and adjusting the parameters of the energy harvesters at the SRs. It is shown that the obtained solutions are efficient in meeting the EH and quality-of-service (QoS) requirements of the SRs and the levels of interference accepted by the PRs. Apart from SWIPT-enabled CRNs, relay-assisted SWIPT networks are envisioned to be a promising framework offering extended coverage, diversity gains, and enhanced energy efficiency. In this case, the relay network itself can benefit from the relayed transmissions in terms of saving energy, and the harvested energy can be used to charge relay nodes and extend their lifetime as compensation for their role of data forwarding. Nonetheless, a concrete performance analysis on the impact of the involved system parameters such as, the energy conversion efficiency and the location of the EH relay terminal, on the trade-off between the achievable information transfer efficiency and the harvested energy level is crucial for the successful implementation of SWIPT in this context. This inspired the research work in the next two contributions with the main focus on developing novel comprehensive analytical frameworks for the investigation and evaluation of SWIPT relaying systems. Specifically, the second contribution is dedicated to examining the application of noncoherent modulation, which is recognised as an energy efficient modulation scheme for SWIPT, due to its ability to eliminate the need of instantaneous channel state information (CSI) estimation/tracking. Through adopting a moments-based approach, novel expressions are derived for the outage probability, achievable throughput, and average symbol error rate (ASER) of dual-hop SWIPT relaying systems. Furthermore, new asymptotic analytical results are derived for the high SNR regime and are then utilised to analytically quantify the achievable diversity order. The proposed mathematical tools are demonstrated to be an accurate and efficient means by which one can conduct a thorough analysis on the system performance without the burden of Monte Carlo simulations. Finally, the third contribution focuses on SWIPT relaying systems operating in the presence of impulsive non-Gaussian noise, which is typical in several practical scenarios. Several studies show sufficient evidences that impulse man-made noise is encountered in various metropolitan, indoor, and underwater wireless applications. Examples of these sources include automotive ignition, electronic devices, household appliances, medical equipment, and industrial equipment. To characterise the behavior of the system performance under this type of noise, an efficient analytical framework is developed where novel closed-form xpressions for the pairwise error probability (PEP) are derived for two relaying schemes, namely, blind relaying and CSI-assisted relaying, employed under two assumptions imposed on the deployed EH process; namely, instantaneous EH (IEH) and average EH (AEH). Apart from being accurate, the derived expressions are shown to be efficient in quantifying the diversity order of the system and providing a comprehensive study on the impact of the severity of impulsive noise on the behavior of the system.

We study the performance of cognitive Underlay System (US) that employ power control mechanism at the Secondary Transmitter (ST) from a deployment perspective. Existing baseline models considered for performance analysis either assume the knowledge of involved channels at the ST or retrieve this information by means of a band manager or a feedback channel, however, such situations rarely exist in practice. Motivated by this fact, we propose a novel approach that incorporates estimation of the involved channels at the ST, in order to characterize the performance of the US in terms of interference power received at the primary receiver and throughput at the secondary receiver (or \textit{secondary throughput}). Moreover, we apply an outage constraint that captures the impact of imperfect channel knowledge, particularly on the uncertain interference. Besides this, we employ a transmit power constraint at the ST to classify the operation of the US in terms of an interference-limited regime and a power-limited regime. In addition, we characterize the expressions of the uncertain interference and the secondary throughput for the case where the involved channels encounter Nakagami-$m$ fading. Finally, we investigate a fundamental tradeoff between the estimation time and the secondary throughput depicting an optimized performance of the US.

In this paper, we investigate the effective capacity of opportunistic spectrum sharing with generalized selection combining (GSC) diversity at the secondary receiver in fading environments. In particular, we study the impact of outdated channel information between the secondary transmitter and the primary receiver on the performance of the secondary user. An exact closed-form expression for the effective capacity of the secondary user with GSC diversity is derived under the peak interference constraint at the primary receiver. Comparisons done using simulations show the effect of the uncertainty of channel information on the effective capacity. Specially, the performance gap due to imperfect channel information becomes smaller with the increase of the number of selected antennas {k}. Theoretic analysis and simulations show that the system performance is robust against imperfect channel information and selection combining (SC) should be adopted under strict delay quality of service (QoS) requirements.

This paper studies optimal power control policies that maximize the achievable rates of underlay cognitive radio systems with arbitrary input distributions under both peak/average transmit power and peak/average interference power constraints for general fading distributions. In particular, optimal power adaptation schemes are formulated and low-complexity optimal power control algorithms are proposed. Additionally, simpler approximations of optimal power control policies in the low-power regime are determined. By considering gamma distributed channel power gains of the interference link between the secondary transmitter and the primary receiver and of the transmission link between the secondary transmitter and the secondary receiver, closed-form expressions for the maximum achievable rate attained with optimal power control in the low-power regime are provided. Through numerical results, the impact of the fading severity of both interference and transmission links and transmit power and interference power constraints on the maximum achievable rate of the cognitive user for different practical constellations and Gaussian signals are investigated.

This paper investigates a multiple users cooperative cognitive non‐orthogonal multiple access (NOMA) network with energy harvesting. Primary transmitter and secondary sources serving as energy‐constrained nodes harvest energy from the power beacon PBS. In primary network, primary transmitter sends signals towards primary receiver. In order to make full use of spectrum resources, the secondary network access the licensed spectrum of primary network with overlay mode, where the best secondary source with maximum transmission signal‐to‐noise ratio between primary transmitter and secondary sources act as relays to forward signal via NOMA principle. In this context, two cooperative transmission protocols, namely, traditional NOMA cooperative transmission and adaptive NOMA cooperative transmission are proposed. For NOMA cooperative transmission, relays use NOMA to forward the superimposed signal of primary signal and secondary signal without any constrain. However, for adaptive NOMA cooperative transmission, relays use NOMA by judging whether the transmission between primary transmitter and primary receiver is successful or not. Primary receiver merges signals received from two transmission slots by selection combining. Finally, exact and asymptotic outage probability of primary network and secondary network with two cooperative transmissions are derived and simulated. It is shown that outage performance is improved for the proposed adaptive NOMA cooperative transmission.