认知无线网络中的无线资源分配研究
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摘要
随着移动用户需求的快速增长,未来无线通信网络面临着无线频谱资源短缺的挑战。固定频谱分配和利用方式虽然避免了无线通信网络间的干扰,但是由于用户和业务分布的不均衡性和突发性等特性,其频谱利用率很低,频谱资源短缺和频谱利用率低下的矛盾十分突出。动态频谱分配和利用观念的提出是为了解决由固定频谱分配方式造成的频谱利用率低下的问题。通过动态频谱分配和利用,网络可以根据业务量需求,动态的对频谱进行分配和利用,以解决大业务量时的频谱短缺和小业务量时的频谱资源浪费问题。认知无线网络被认为是实现动态频谱分配和利用的关键技术,其通过对外部环境中的频谱状态信息进行认知,可以在保护具有授权频谱的主用户服务质量的前提下智能的对频谱进行动态的接入和利用。本文主要针对认知无线网络关键技术之一的无线资源分配进行研究。无线资源分配在复杂的无线信道衰落特性、干扰及用户业务分布不均匀的情况下,通过灵活的分配多维无线资源,如频谱、功率、速率等,以尽可能有效的利用这些无线资源来提升频谱利用率等系统性能指标。
首先,本文研究了认知无线网络中的功率分配：针对非理想信道状态信息下的功率分配问题,提出了同时考虑信道状态信息存在错误估计误差和反馈时延,以最大化遍历容量和中断容量为目标的最优功率分配算法。该功率分配算法能很好的保护主用户免受由于非理想信道状态信息带来的额外干扰。通过理论分析得到了遍历容量和中断容量的表达式,完善了现有非理想信道状态信息下的容量理论分析,并为分析非理想信道状态信息对于认知无线网络容量的影响提供了理论支撑；以最小化认知无线网络的误比特率为目标,提出了在不同的发射功率和干扰功率约束组合下的最优功率分配算法。该算法相比传统的注水功率分配算法能达到更低的误比特率。
其次,本文研究了时延服务质量约束下的认知无线网络联合功率和速率分配,分别提出了理想信道状态信息和非理想信道状态信息下的最大化有效容量的最优联合功率和速率分配算法。提出的联合分配算法可以很好的保证次用户的时延服务质量需求。进而通过理论推导,分别得到了理想信道状态信息、最大比合并下的有效容量表达式和非理想信道状态信息下的有效容量表达式,为分析各种系统参数对于认知无线网络有效容量的影响提供了理论支撑。
再次,本文研究了认知无线网络中的联合信道和功率分配：提出了主用户和次用户存在有限合作的情况下的低复杂度、近最优的联合信道和功率分配算法。该算法性能相比非合作的联合信道和功率分配算法大大提升,且其性能非常接近最优算法的性能,但其复杂度相比最优算法大大下降；针对现有研究中对于次用户公平性主要关注于速率公平的问题,提出了资源公平约束下的联合信道和功率分配算法。该算法通过改变分配给次用户的最小和最大信道数约束,灵活的调节次用户间的公平性,相比以速率作为公平性衡量指标的分配算法,其实现更加灵活。
最后,本文研究了认知无线网络中的联合信道、功率和速率分配：提出了最小化认知无线多播网络中断概率的联合信道、功率和速率分配算法。算法中既考虑了多播组的加权中断概率,也考虑了多播组中次用户的加权中断概率。分析了多种系统参数对于认知无线多播网络中断概率的影响,为认知无线多播网络的实际部署提供了参考；针对同时具有时延敏感和时延不敏感异构业务的认知无线网络,提出了最小化认知无线网络发射功率消耗的联合信道、功率和速率算法。该算法复杂度低,实现简单,且性能相比传统的分配算法在更好的保证次用户的服务质量需求的前提下,发射功率消耗更低。
In recent years, with the increase of rquirements of mobile users, the fu-ture wireless communication networks face the problem of spectrum scarcity. Although the fixed spectrum allocation and usage avoids the interference be-tween wireless networks, its spectrum efficiency is very low due to the uneven and suddenness of the distribution of users and services, which causes the con-flict between the spectrum scarcity and low spectrum efficienty. The concept of dynamic spectrum allocation and usage is proposed to solve the problem of low spectrum efficiency caused by fixed spectrum allocation. Through dy-namic spectrum allocation and usage, wireless networks can allocate and use spectrum according to service requests, and further solve the problem of spec-trum scarcity with heavy service load and the problem of spectrum waste with light service load. Cognitive wireless network is believed to be one of the key technologies to achieve dynamic spectrum allocation and usage. It can acquire spectrum status information by cognitive methods, then dynamically access and use spectrum as long as the quality of service of primary users on the licensed spectrum is protected. This thesis focuses on the radio resource allocation re-search, which is one of the key technologies in the cognitive wireless network. Radio resource allocation is used to allocate radio resources, e.g., spectrum, power, rate, in the complex wireless channel fading environment, interference and uneven user distribution, in order to efficiently use these radio resources to improve system performance indicators such as spectrum efficiency.
Firstly, this thesis investigates the problem of power allocation in cognitive wireless network. For the problem "of power allocation with imperfect channel state information, we propose optimal power allocation algorithms to maximize ergodic capacity and outage capacity, respectively, taken both channel estima-tion errors and feedback delay into consideration. The proposed power alloca- tion algorithms can well protect the primary user transmission due to imperfect channel state information. Closed-form expressions for ergodic capacity and outage capacity are derived, which complete the existing capacity results anal-ysis with imperfect channel state information. Aiming at minimizing bit errir rate of cognitive wireless network, we propose the optimal power allocation algorithms under various transmit power and interference power constraints, which can provide lower bit error rate than that of waterfill power allocation algorithm.
Secondly, this thesis investigates the problem of joint power and rate al-location in cognitive wireless network under the delay quality of service con-straint. We propose the optimal joint power and rate allocation algorithms to maximize the effective capacity with the perfect channel state information and imperfect channel state information, respectively. The proposed algorithms can well protect the delay quality of service of secondary users. The expression for the effective capacity with perfect channel state information and maximum ra-tio combining as well as the expression for the effective capacity with imperfect channel state information are also derived.
Thirdly, this thesis investigates the problem of joint channel and power allocation in cognitive wireless network. We propose a low complexity and close optimal joint channel and power allocation algorithm with primary user-s'limited cooperation. The performance of the proposed algorithm is great-ly improved compared with that of the non-cooperative algorithm and is very close to that of the optimal cooperative algorithm with much lower complexi-ty. Considering the fact that most of the studies focus on rate fairness between secondary users, we proposed joint channel and power allocation algorithms based on resource fairness constraint. The proposed algorithms can flexibly adjust the fairness between secondary users through regulating the allocated minimum and maximum number of channels constraints.
Lastly, this thesis investigates the problem of joint channel, power and rate allocation in cognitive wireless network. Aiming at minimizing the outage probability for cognitive wireless multicast network, we propose joint channel, power and rate allocation algorithms. The proposed algorithms consider two types of outage probabilities, i.e., group outage probability and individual out-age probability. The impacts of various system parameters on the outage prob-abilities for cognitive wireless multicast network are also investigated. For the scenario that there are heterogeneous services, i.e., delay-sensitive and delay-insensitive services, provided by cognitive wireless network, an efficient joint channel, power and rate allocation algorithm is proposed to minimize the trans-mit power consumption of cognitive wireless network. Compared with existing algorithms, the proposed algorithm provides lower transmit power consump-tion while guaranteeing the quality of service of secondary users.
首先,本文研究了认知无线网络中的功率分配：针对非理想信道状态信息下的功率分配问题,提出了同时考虑信道状态信息存在错误估计误差和反馈时延,以最大化遍历容量和中断容量为目标的最优功率分配算法。该功率分配算法能很好的保护主用户免受由于非理想信道状态信息带来的额外干扰。通过理论分析得到了遍历容量和中断容量的表达式,完善了现有非理想信道状态信息下的容量理论分析,并为分析非理想信道状态信息对于认知无线网络容量的影响提供了理论支撑；以最小化认知无线网络的误比特率为目标,提出了在不同的发射功率和干扰功率约束组合下的最优功率分配算法。该算法相比传统的注水功率分配算法能达到更低的误比特率。
其次,本文研究了时延服务质量约束下的认知无线网络联合功率和速率分配,分别提出了理想信道状态信息和非理想信道状态信息下的最大化有效容量的最优联合功率和速率分配算法。提出的联合分配算法可以很好的保证次用户的时延服务质量需求。进而通过理论推导,分别得到了理想信道状态信息、最大比合并下的有效容量表达式和非理想信道状态信息下的有效容量表达式,为分析各种系统参数对于认知无线网络有效容量的影响提供了理论支撑。
再次,本文研究了认知无线网络中的联合信道和功率分配：提出了主用户和次用户存在有限合作的情况下的低复杂度、近最优的联合信道和功率分配算法。该算法性能相比非合作的联合信道和功率分配算法大大提升,且其性能非常接近最优算法的性能,但其复杂度相比最优算法大大下降；针对现有研究中对于次用户公平性主要关注于速率公平的问题,提出了资源公平约束下的联合信道和功率分配算法。该算法通过改变分配给次用户的最小和最大信道数约束,灵活的调节次用户间的公平性,相比以速率作为公平性衡量指标的分配算法,其实现更加灵活。
最后,本文研究了认知无线网络中的联合信道、功率和速率分配：提出了最小化认知无线多播网络中断概率的联合信道、功率和速率分配算法。算法中既考虑了多播组的加权中断概率,也考虑了多播组中次用户的加权中断概率。分析了多种系统参数对于认知无线多播网络中断概率的影响,为认知无线多播网络的实际部署提供了参考；针对同时具有时延敏感和时延不敏感异构业务的认知无线网络,提出了最小化认知无线网络发射功率消耗的联合信道、功率和速率算法。该算法复杂度低,实现简单,且性能相比传统的分配算法在更好的保证次用户的服务质量需求的前提下,发射功率消耗更低。
In recent years, with the increase of rquirements of mobile users, the fu-ture wireless communication networks face the problem of spectrum scarcity. Although the fixed spectrum allocation and usage avoids the interference be-tween wireless networks, its spectrum efficiency is very low due to the uneven and suddenness of the distribution of users and services, which causes the con-flict between the spectrum scarcity and low spectrum efficienty. The concept of dynamic spectrum allocation and usage is proposed to solve the problem of low spectrum efficiency caused by fixed spectrum allocation. Through dy-namic spectrum allocation and usage, wireless networks can allocate and use spectrum according to service requests, and further solve the problem of spec-trum scarcity with heavy service load and the problem of spectrum waste with light service load. Cognitive wireless network is believed to be one of the key technologies to achieve dynamic spectrum allocation and usage. It can acquire spectrum status information by cognitive methods, then dynamically access and use spectrum as long as the quality of service of primary users on the licensed spectrum is protected. This thesis focuses on the radio resource allocation re-search, which is one of the key technologies in the cognitive wireless network. Radio resource allocation is used to allocate radio resources, e.g., spectrum, power, rate, in the complex wireless channel fading environment, interference and uneven user distribution, in order to efficiently use these radio resources to improve system performance indicators such as spectrum efficiency.
Firstly, this thesis investigates the problem of power allocation in cognitive wireless network. For the problem "of power allocation with imperfect channel state information, we propose optimal power allocation algorithms to maximize ergodic capacity and outage capacity, respectively, taken both channel estima-tion errors and feedback delay into consideration. The proposed power alloca- tion algorithms can well protect the primary user transmission due to imperfect channel state information. Closed-form expressions for ergodic capacity and outage capacity are derived, which complete the existing capacity results anal-ysis with imperfect channel state information. Aiming at minimizing bit errir rate of cognitive wireless network, we propose the optimal power allocation algorithms under various transmit power and interference power constraints, which can provide lower bit error rate than that of waterfill power allocation algorithm.
Secondly, this thesis investigates the problem of joint power and rate al-location in cognitive wireless network under the delay quality of service con-straint. We propose the optimal joint power and rate allocation algorithms to maximize the effective capacity with the perfect channel state information and imperfect channel state information, respectively. The proposed algorithms can well protect the delay quality of service of secondary users. The expression for the effective capacity with perfect channel state information and maximum ra-tio combining as well as the expression for the effective capacity with imperfect channel state information are also derived.
Thirdly, this thesis investigates the problem of joint channel and power allocation in cognitive wireless network. We propose a low complexity and close optimal joint channel and power allocation algorithm with primary user-s'limited cooperation. The performance of the proposed algorithm is great-ly improved compared with that of the non-cooperative algorithm and is very close to that of the optimal cooperative algorithm with much lower complexi-ty. Considering the fact that most of the studies focus on rate fairness between secondary users, we proposed joint channel and power allocation algorithms based on resource fairness constraint. The proposed algorithms can flexibly adjust the fairness between secondary users through regulating the allocated minimum and maximum number of channels constraints.
Lastly, this thesis investigates the problem of joint channel, power and rate allocation in cognitive wireless network. Aiming at minimizing the outage probability for cognitive wireless multicast network, we propose joint channel, power and rate allocation algorithms. The proposed algorithms consider two types of outage probabilities, i.e., group outage probability and individual out-age probability. The impacts of various system parameters on the outage prob-abilities for cognitive wireless multicast network are also investigated. For the scenario that there are heterogeneous services, i.e., delay-sensitive and delay-insensitive services, provided by cognitive wireless network, an efficient joint channel, power and rate allocation algorithm is proposed to minimize the trans-mit power consumption of cognitive wireless network. Compared with existing algorithms, the proposed algorithm provides lower transmit power consump-tion while guaranteeing the quality of service of secondary users.
引文
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