Optimal and suboptimal adaptive algorithms for rate and power transmission in OFDM-based Cognitive Radio systems☆
Graphical abstract
Introduction
With the rapid growth of wireless technology and increase in the number of wireless users, the frequency spectrum is becoming a more and more rare resource [1]. The Federal Communication Commission spectrum policy task force has reported that the traditional frequency band allocation to users may be inefficient, because the demands of frequency band highly vary along space or time domains [2]. CR has been proposed as a novel technology to enhance spectral efficiency by exploiting frequency holes in dynamically varying environments [3], [4].
Adaptive resource allocation is a powerful technique to improve the performance and spectrum efficiency in a CR [5]. Using adaptive resource allocation, a CR can change its transmission power and modulation level based on spectrum bands of PUs and fading channel variations to maximize the achievable capacity of SU [6]. Due to the coexistence of the PU and SU in adjacent spectrums, Adjacent Channel Interference (ACI) is introduced in both PU and SU transceivers and thus decreasing their performances. Therefore, the transmission power of Secondary User Transmitter (SUT) must be less than the power budget. Also, the amount of interference introduced by a SUT on a Primary User Receiver (PUR) must be less than an interference power threshold [7].
Considering the high advantage of dynamically allocation of frequency holes, OFDM is a proper modulation scheme for the SUs [3], [4]. In order to improve the system performance in OFDM-based Cognitive Radio systems, modulation level and power needs to be adaptively assigned to each subcarrier according to its subcarrier state variation [8]. More powers and bits per symbol must be allocated to the subcarrier with higher channel fading gain, and less powers and bits per symbol to noisy subcarrier [9]. Adaptive modulation and bit loading are efficient techniques for reliable transmission [10]. The concept of adaptive modulation is to match the modulation type and modulation level to channel state variation [11]. The basic idea behind adaptive modulation is to guarantee that the most effective mode is always used over channel state variation [12]. Adaptive power allocation scheme changes the allocated power to fading channel states while satisfying the Bit Error Rate (BER) requirement [11].
The current study investigates the Multi-Quadrature Amplitude Modulation (M-QAM) adaptive modulation and power allocation in an OFDM-based CR system to maximize the overall transmission rate of the SU. From the study conducted in [13], if perfect channel state information is available in SUT, a superior power allocation policy can be designed for SU so that to improve the performance of a CR system. Therefore, it is assumed perfect channel state information is available in SUT and the SUT is aware of instantaneous channel power gain between SUT and Secondary User Receiver (SUR) and channel power gain between SUT and PUR. Similar to [14], it is also assumed that different PURs can impose different interference threshold constraints to the CR system. Additionally, the study was expanded on the behavior of uniform loading and water filling algorithms. Due to complexity of optimal algorithm and low efficiency of uniform loading and water filling algorithms, a novel suboptimal power loading algorithm is suggested; thus the calculation of the maximum modulation level can be allocated to each subcarrier according to the allocated power. In the proposed suboptimal algorithm, the allocated power and modulation level of SU at each subcarrier are obtained adaptively based on several factors including; channel path gain between SUT and SUR, channel path gains between SUT and PURs, interference threshold, spectral distance between ℓth bands of PU and ith subcarrier of SU and noise variance and interference introduced by PUs on subcarrier of SU. Finally, the proposed suboptimal algorithm is compared to the optimal, uniform loading and water filling algorithms. Simulation results indicated that the proposed algorithm had a better performance than conventional power loading algorithms for the OFDM-based system including water filling and uniform loading. Also, it is found that the complexity of the proposed suboptimal algorithm is less than the optimal algorithm.
Subsequently the current study proceeds further as follows: Section 2 presents related works and Section 3 presents the system model, while Section 4 describes the problem formulation. In Section 5, a suboptimal algorithm system is suggested and Section 6 describes two conventional power allocation algorithms in OFDM-based systems, including uniform loading and water filling. Numerical results are presented in Section 7 and the paper is concluded in Section 8.
Section snippets
Related works
Due to complexity of optimal solution, it is difficult or rather impossible to use the optimal method in practice. Furthermore, due to low efficiency of conventional methods of allocated power in OFDM systems such as uniform loading and water filling algorithms, these methods may not be suitable for use in OFDM- based CR systems. In [2] authors introduced a method to calculate the allocated power to subcarriers if both the SU and PU use the same OFDM system. In some scenario, a CR user and L
System model
It is assumed that the spectrum has already been allocated and that a SU coexists with L PUs in adjacent spectrums as illustrated in Fig. 1 (similar to system model is used in [3], [4], [14]). The bandwidth of the SU is divided into N flat independent subcarriers each having a bandwidth of Δf, which is less than the coherence bandwidth of the channel. The L PUs are supposed to be inhabiting spectrums of bandwidth B1, B2, … , BL. giss is the channel path gain between the SUT and SUR over the ith
Problem formulation
Adaptive modulation and power transmission can adjust the transmission power and rate for SU systems and improve the spectrum efficiency. Since the allocated power to SUT should not decrease the Quality of Service (QOS) of the PU, a constraint was considered on the interference power introduced by SUT at the PUR. Also, in practice, the transmission power of SU needs to be restricted according to the operating range of powers. Therefore, it is considered the problem of maximizing the overall
Suboptimal algorithm
The power has to be allocated to the SU’s subcarriers so that to maximize the SU’s total transmission rate, while satisfying all the L + 1 constraints specified in Eqs. (8), (9). In the optimal algorithm, all the L + 1 constraint was considered simultaneously, while in the proposed suboptimal algorithm only one constraint is kept and the transmission power in each subcarrier is determined.
In the proposed suboptimal algorithm, the power allocated to each subcarrier is proportional to the channel
Uniform loading
In this algorithm, equal power is allotted in each subcarrier so that all constraints can be satisfied. Solving Eq. (8) to fulfill the strict equality on the ℓth interference constraint, the transmission power of the uniform loading algorithm to satisfy the ℓth interference constraint in the Eq. (8) can be obtained from [14]:The transmission power to satisfy total power constraint in Eq. (9) can be written as:The final allocated power to ith subcarrier
Numerical results
In this section, a numerical example is presented for the proposed system to compare the proposed suboptimal algorithm with optimal, uniform loading and water filling algorithms. It is assumed that the values of the number of primary users (L) and the number of OFDM subcarriers (N) are 2 and 6, respectively. The values of Ts, Δf, B1 and B2 are 4 μs, 0.3125 MHz, 1 MHz and 2 MHz, respectively. The value of AWGN variance is 10−8 W. The channel path gains are modeled by Rayleigh distribution. The
Conclusions
A novel suboptimal power loading algorithm was proposed and formulated by analyzing an optimal adaptive rate and power loading algorithm for an OFDM-based Cognitive Radio system. Results of the allocated power obtained from different algorithms were used by Eq. (3) to calculate the maximum modulation level. Simulation results indicated that the maximum achievable total transmission rate of the suboptimal algorithm was greater than water filling and uniform loading algorithms. The optimal
Acknowledgement
The authors wish to acknowledge the help and financial support provided by the Research Institute to accomplish the study for ICT in Iran, Tehran.
Reza Khederzadeh received the B.S. degree in electrical engineering from Shahid Chamran University, Ahvaz, Iran, in 2010 and the M.S. degree in communication engineering from Birjand University, Birjand, Iran, in 2012. His current research interests include resource scheduling and management, cognitive radio and cooperative communications.
References (18)
- et al.
Power allocation for a mobile secondary user in OFDM-based cognitive radio
Int J Digital Content Technol Appl
(2011) - et al.
Power/Bit loading in OFDM-based cognitive networks with comprehensive interference considerations: the single-SU case
IEEE Trans Veh Technol
(2010) - et al.
Optimal and suboptimal power allocation schemes for OFDM-based cognitive radio systems
IEEE Trans Wireless Commun
(2008) - et al.
An efficient power-loading scheme for OFDM-based cognitive radio systems
IEEE Trans Veh Technol
(2010) - et al.
Adaptive rate and power transmission in spectrum-sharing systems with statistical interference constraint
IET Commun
(2014) - et al.
Resource management in spectrum-sharing cognitive radio broadcast channels: adaptive time and power allocation
IEEE Trans Commun
(2011) - Weiss T, Hillenbrand J, Krohn A, Jondral FK. Mutual interference in OFDM-based spectrum pooling systems. In: IEEE...
- et al.
Adaptive modulation for limited diversity fading channels
Commun IET
(2009) - et al.
Distributed approach for power and rate allocation to secondary users in cognitive radio networks
IEEE Trans Veh Technol
(2011)
Cited by (6)
Cooperative weighted-fair control strategy for spectrum self-coexistence in multi-cell WRAN systems
2015, Computers and Electrical EngineeringCitation Excerpt :To enable efficient coexistence, SUs must perform spectrum sensing to determine idle channels, spectrum decision to select the best idle channel/channels, spectrum sharing to coordinate access among SUs, and spectrum mobility to vacate the occupied channel/channels when a licensed user appears. Specifically, SUs should have a cognitive capability to sense the RF environment, a self-organizing capability to analyze and learn from the sensed information and a reconfigurable capability to adapt their operating parameters according to the surrounding RF environment [1–5]. The IEEE 802.22 standard for a Wireless Regional Area Network (WRAN) system is considered as the first wireless standard based on CR technology.
Adaptive resources assignment in OFDM-based cognitive radio systems
2019, International Journal of Electrical and Computer EngineeringResource allocation in MIMO systems specific to radio communication
2019, Archives of Electrical EngineeringOFDM for cognitive radio systems: Novel power allocation and bit loading algorithms
2019, International Journal of Electronics and TelecommunicationsMinimum BER power allocation for ofdm-based cognitive radio networks
2015, KSII Transactions on Internet and Information Systems
Reza Khederzadeh received the B.S. degree in electrical engineering from Shahid Chamran University, Ahvaz, Iran, in 2010 and the M.S. degree in communication engineering from Birjand University, Birjand, Iran, in 2012. His current research interests include resource scheduling and management, cognitive radio and cooperative communications.
Hamid Farrokhi received the M.S. degree in electronics engineering from Iranian University of Science and Technology (IUST) in 1996 and Ph.D. degree (with distinction) from University of Regina, Canada in 2005. He is currently an associate professor at the University of Birjand, Iran. His current research interests include spread spectrum systems, wireless CDMA networks, channel coding, and cognitive radio.
- ☆
Reviews processed and recommended for publication to the Editor-in-Chief by Associate Editor Dr. Sabu Thampi.