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Resource Management in Cognitive Radio Network and
Heterogeneous Networks
Yinghao Zhang
Abstract: In this paper, power control, spectrum sharing and spectrum sensing in cognitive wireless
point networks are learned, and the existing representative research results are reviewed. These
studies provide theoretical and technical support for improving the utilization rate of spectrum
resources and realizing spectrum reuse. In addition, this paper also studies the typical application of
power control and power allocation in heterogeneous networks.
1.Power control in cognitive radio network
Zhao et al. [1] address the power control problems of Cognitive Radio (CR) under transmission
power and interference temperature constraints. First, the authors propose the interference constraint
which ensures that the Quality of Service (QoS) standards for primary users is considered and a
non-cooperative game power control model. Based on the proposed model, they developed a logical
utility function based on the Signal-to-Interference-Noise Ratio (SINR) and a novel algorithm that
is suitable for CR network power control. Then, the existence and uniqueness of the Nash
Equilibrium (NE) in our utility function are proved by the principle of game theory and the
corresponding optimizations. Compared to traditional algorithms, the proposed one could converge
to an NE in 3-5 iterative operations by setting an appropriate pricing factor. Finally, simulation
results verified the stability and superiority of the novel algorithm in flat-fading channel
environments.
In [2], a centralized spectrum sharing model with interference temperature limited is
considered, and the power allocation problem under interference temperature limitations of multi-
user access is also analyzed. Corresponding theoretical model is derived and the transformation
problem from power allocation to a nonlinear programming is also obtained by the practical model
of multi-users. Consequently, the improved simulated annealing genetic algorithm can be applied
to solve this nonlinear programming problem. As the simulated annealing genetic algorithm has the
advantages of combined local search and global search ability, it can get faster convergence to the
optimal level when the transmitter number increasing quickly, so that all the transmitter power can
meet the cognitive network stable convergence properties. In this paper, the spectrum shared user
network with only one primary user and some cognitive users is under consideration. However, the
real environment is more complex, the case of multi-cell-aliasing spectrum sharing issues will be
under further study, especially including the network architecture and signaling protocols.
Based on a Space-Time Block Coding Multi-Carrier Code Division Multiple Access (STBC
MC-CDMA) system, an Asynchronous Distributed Pricing (ADP) Algorithm is studied in [3], in
which the cognitive radio (CR) users announces a price that reflect other users' compensation paid.
The power control is implemented by updating pricing and power level. The ADP algorithm is a
distributed power control scheme based on the super modular game theory. Introduced in the STBC
MC-CDMA system, it can improve the capacity and the utility of the system, and show faster
convergence.
2. spectrum sharing in cognitive radio network
In [4], the authors proposed an OFDM spectrum sharing protocol that exploits the situation
when the primary system is incapable of supporting its target transmission rate. In the proposed
protocol, the secondary system gains opportunistic spectrum access by assisting the primary system
to meet its target rate. Specifically, the secondary transmitter opportunistically helps to amplify and
forward the primary signal through a fraction of the secondary subcarriers. The authors proposed an
algorithm to jointly optimize the set of subcarriers used for cooperation [5], subcarrier pairing, and
subcarrier power allocation such that the transmission rate of the secondary system is maximized,
while helping the primary system, as a higher priority, to achieve its target rate. This joint
optimization problem is solved efficiently by using the dual decomposition method. Simulation
results confirmed the efficiency of the proposed spectrum sharing protocol as well as its benefit to
both the primary and secondary systems [6].
In [7], the authors have investigated the resource allocation problem in relay-aided OFDM CR
networks. The SU’s throughput is maximized via joint subcarrier pairing and power allocation.
Meanwhile, the interference from both the secondary source and the SRN to the primary receiver is
kept within an acceptable limit. A suboptimal resource-allocation algorithm was also designed to
reduce computational complexity. The numerical examples demonstrated enhanced performance
compared with trivial resource-allocation algorithms.
3. Spectrum sensing in cognitive radio network
In [8], the authors propose a FD opportunistic spectrum sharing protocol that exploits the
situation when the primary system experiences weak channel conditions. The secondary system,
which can act as a DF relay for the primary system, tries to help the primary system achieve its
target rate by allocating a fraction of its subcarriers to decode and forward primary signal. As a
reward, the secondary system can use a fraction of subcarriers to transmit its own signal in both two
phases, and thus gaining spectrum access. The paper studied the joint optimization of subcarriers
and power allocation such that the transmission rate of secondary system is maximized while
ensuring the primary system to achieve its target rate. Simulation results were presented to show
that the proposed secondary spectrum access scheme can benefit both primary and secondary system.
The development of the IEEE 802.22 WRAN standard aims at using CR techniques to share
the unused spectrums that have been allocated to the television broadcast service [9]. In [10], the
authors have considered cooperative spectrum sensing, which is an important issue in CR [11].
Different from existing works, where each SU transmits its local sensing decision, they have
considered SU transmitting a function of its received signal from the PU, and have optimized the
relaying function at each SU via functional analysis for both average and peak power constraints.
In addition, the authors have discussed optimization of local spectrum sensing with two SUs. The
proposed spectrum-sensing algorithms perform significantly better than existing algorithms. It is
interesting to investigate how to pair nodes in a large network and what is the best strategy for
cooperation among more than two users. In addition, simultaneous consideration of multiple PUs is
in place.
4. Relevant researches in heterogeneous networks
An algorithm of power control in two-tier heterogeneous networks is proposed in [12]. We
consider femtocell base stations (FBSs) dense deployment in the macro-cell base station (MBS)
coverage, the MBS dynamically estimates total uplink interference of femtocell user equipments
(FUEs). In order to cope with interference issues, the MBS decides the transmit power of macro-
cell user equipment (MUE) according to the uplink power budget. In the meanwhile, the interference
pricing mechanism is introduced. We assume that the MBS protects itself by pricing the interference
on each FUEs, so as to achieve the goal of controlling the interference from FUEs. Simulation results
show that the proposed algorithm yields a significant performance improvement in terms of the
channel capacity.
Attributable to the using of the same spectrum resources, heterogeneous cellular networks have
serious interference problems, which greatly restricts the performance of the network. In [13], the
price-based power allocation for femtocells underlaying a macro-cell heterogeneous cellular
network is investigated. By exploiting interference pricing mechanism, we formulate the
interference management problem as a Stackelberg game and make a joint utility optimization of
macro-cells and femtocells. Specially, the energy consumption of macro-cell users and the
transmission rate utility of femtocell users are considered in this utility optimization problem. In the
game model, the macro-cell base station is regarded as a leader, which coordinates the interference
from femtocell users to the macro-cell users by pricing the interference. On the other hand, the
femtocell base stations are modelled as followers. The femtocell users obtain their power allocation
by pricing. After proving the existence of the Stackelberg equilibrium, the non-uniform and uniform
pricing schemes are proposed, and distributed interference pricing algorithm is proposed to address
uniform interference price problem. Simulation results demonstrate that the proposed schemes are
effective on interference management and power allocation.
Conclusion
This paper studies several representative papers in cognitive radio networks, and describes
their contributions in detail. These technological innovations can effectively solve the problems of
insufficient spectrum resources and low utilization rate of spectrum resources. Furthermore, how to
overcome the difficulties of power control and power allocation in heterogeneous networks is
discussed.
Reference
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[2] J. Zhao, X. Guan, X. Li, "Power Allocation Based on Genetic Simulated Annealing Algorithm
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[11] M. S. Hamayun, Y. Gong and J. Zhao, "Cognitive spectrum sensing with the aid of location
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