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认知无线电MIMO广播信道的能效优化策略
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“这篇研究论文探讨了认知无线电MIMO广播信道的能效优化问题,重点关注在单位能量消耗下的系统吞吐量提升。作者是Junling Mao、Gang Xie、Jinchun Gao和Yuanan Liu,他们都是IEEE的会员。” 在无线通信领域,认知无线电(CR)技术因其对频谱资源的有效利用而受到广泛关注。传统的认知无线电MIMO(Multiple-Input Multiple-Output)系统设计主要侧重于提高系统吞吐量,但随着环保意识的增强和能源效率(EE)成为关键考量因素,本研究论文旨在认知无线电MIMO广播信道(BC)中优化能源效率,同时确保单位能量消耗下的系统性能。 论文研究的问题是在总功率约束、干扰功率约束以及最小系统吞吐量约束下,如何优化认知无线电MIMO BC的能源效率。由于这是一个非凸优化问题,解决起来颇具挑战性。为了找到最优解,作者将原问题转换为一个等价的一维问题,其目标函数近似为凹函数,并采用黄金分割法进行求解。这种方法有助于在满足约束条件的同时,有效地平衡系统性能与能耗之间的关系。 黄金分割法是一种数值优化方法,它通过在区间内不断分割并比较函数值来逼近最优解,具有较高的精度和收敛性。在仿真结果中,论文展示了所提出的算法在实现能效优化方面的有效性。 关键词包括:能源效率、认知无线电、MIMO广播信道和功率分配。这篇论文的贡献在于为认知无线电系统提供了一种新的优化策略,即在保证服务质量的前提下,更有效地利用能源,这对未来绿色通信和可持续发展的无线网络设计具有重要意义。
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IEEE COMMUNICATIONS LETTERS, VOL. 17, NO. 2, FEBRUARY 2013 337
Energy Efficiency Optimization for
Cognitive Radio MIMO Broadcast Channels
Junling Mao, Gang Xie, Member, IEEE, Jinchun Gao, Member, IEEE, and Yuanan Liu, Member, IEEE
Abstract—Conventional designs of cognitive radio (CR)
multiple-input multiple-output (MIMO) systems mainly focus
on the system throughput. Since nowdays the energy efficiency
(EE) of wireless systems has become more and more important,
this paper intends to improve the system throughput for unit-
energy consumption in CR MIMO broadcast channels (BC). The
EE optimization problem of CR MIMO BC is studied under
the total power constraint, the interference power constraint
and the minimum system throughput constraint. Since the EE
optimization problem is non-convex, in order to find the optimal
solution, we transform it into an equivalent one-dimension
problem with a quasi-concave objective function and use the
golden section method to solve it. Through simulations, we show
the efficiency of the proposed algorithm.
Index Terms—Energy efficiency, cognitive radio, MIMO broad-
cast channels, power allocation.
I. Introduction
C
OGNITIVE Radio (CR) technique is first introduced by
Mitola [1] and has drawn considerable attentions due
to its advantage of spectrum reusing. In CR networks, the
secondary networks usually communicate over the spectrum
originally allocated to primary networks while ensuring that
the performance degradation of the active primary transmis-
sions is tolerable [2].
Recently, the multiple antennas technique is introduced to
CR networks to improve the system throughput of secondary
systems [3]. [4] and [5] give the optimal power allocation for
CR MIMO broadcast channels (BC) based on the dirty paper
coding (DPC) scheme [6] which can achieve the capacity of
MIMO BC [7]. Since the power allocation problem of CR
MIMO BC is non-convex, [4] and [5] solve it via the multiple
access channels (MAC) - BC duality of CR MIMO BC.
Besides the system throughput (or the spectrum efficiency
(SE)), the energy efficiency (EE) (or the system throughput
for unit-power consumption) has been considered more and
more important in future wireless systems [8][9][10]. The EE
optimization problem of non-CR MIMO BC has been solved
in [11] based on the fractional programming theory, the convex
optimization theory [12] and the MAC-BC duality of non-CR
MIMO BC. However, the EE optimization problem of CR
Manuscript received October 22, 2012. The associate editor coordinating
the review of this letter and approving it for publication was W. Zhang.
This work was supported in part by Canada-China Scientific and Techno-
logical Cooperation (No. 2010DFA11320), the Natural Science Foundation of
China (Nos. 60973111 and 61170275), and Important National Science and
Technology Specific Projects (No. 2012ZX03003001-004).
J. Mao, J. Gao. and L. Liu are with the Beijing Key Laboratory of Work
Safety Intelligent MonitoringBeijing University of Posts and Telecommuni-
cations, Beijing 100876, China (e-mail: maojunling@bupt.edu.cn).
G. Xie is with the Beijing Key Laboratory of Network System Architecture
and Convergence, Beijing University of Posts and Telecommunications.
Digital Object Identifier 10.1109/LCOMM.2012.121912.122351
DPC
Secondary Transmitter
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Fig. 1. The system model of CR MIMO BC.
MIMO BC is still unsolved in previous works.
In this paper, we study the EE optimization of CR MIMO
BC based on the MAC-BC duality of CR MIMO BC.
To protect the primary transmission, both the total power
constraint and the individual interference power constraint
applied at each primary receiver are considered. Since the
EE optimization of MIMO BC is more complicated than that
of non-CR MIMO BC, the optimization method used in this
paper is totally different from the method used in [11]. In this
paper, an equivalent one-dimension optimization problem with
quasi-concave objective function is constructed to solve the EE
optimization problem of CR MIMO BC. Note that although
the method used in this paper is similar to the method in [13]
which also constructs an equivalent problem to optimize EE,
the proposed method has wider applicability since it does not
restrict the concavity and differentiability of the rate function.
The rest of paper is organized as follows. Section II provides
the system model of CR MIMO BC. Section III presents
the optimal power allocation scheme. The simulation results
and conclusions are given in Section IV and Section V
respectively.
The following notations are used in this paper. |·| denotes the
determinant,
(
·
)
†
denotes the conjugate transpose and A 0
means that A is semi-definite positive. The identity matrix
is denoted by I. The distribution of a circularly-symmetric-
complex-Gaussian (CSCG) matrix with the mean Z and the
covariance Σ is denoted by CN
(
Z, Σ
)
.
II. System Model
This paper considers the CR MIMO BC as shown in Fig.
1, where one secondary transmitter (ST) and K secondary
receivers (SRs) share the spectrum with N primary users (PUs)
1089-7798/13$31.00
c
2013 IEEE
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