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With the rapid development of 5G NR (New Radio), the explosive increment of traffic amount is calling the utilization of unlicensed band. 3GPP has proposed LAA (Licensed Assisted Access) to use LTE in unlicensed band and pointed out that NR-U (NR-Unlicensed) can reuse most designs of it. However, the existing channel access mechanism of LAA is conservative under the coexistence scenario of NR-U, which leads to the waste of time resource. To address the problem this paper proposes a hybrid channel access mechanism to take advantage of the LBT (Listen-Before-Talk) mechanism of LAA when channel is quite busy and transmit directly with reduced power when it is relatively idle. The channel busy degree is judged by a series of periodically updated adaptive thresholds. System-level simulation verifies that under the coexistence scenario of NR-U the proposed mechanism can achieve higher UPT (User Perceived Throughput) and lower delay than other channel access mechanisms.

High power to guarantee strict performance requirement and low power to avoid energy depletion result in an inevitable conflict for a renewable energy harvesting communication system with finite energy storage. This paper proposes a generic approach to study the per-flow performance in such a multichannel system multiplexed by multiple flows. The queueing delay constraint and energy storage constraint are constructed to express the probabilistic bound of queuing delay and that of energy depletion, respectively. We study these constraints with the statistical information of the processes, including traffic arrivals and service, energy harvesting, and consumption. The lower bound of the long-term maximum per-flow throughput is then derived to meet the constraints under a specific system. The accuracy of the proposed approach is validated by simulation experiments. The analysis reveals how the sustained throughput is affected by various factors, such as the queueing delay and energy storage constraints, the packet size, the energy block size, the traffic scheduling schemes, the bandwidth allocation schemes as well as the interdependence among the channel service processes. Particularly, the analysis also provides valuable insight into traffic admission control from the viewpoint of small queueing delay and finite energy storage.

Alzheimer’s disease (AD) is the most common neurodegenerative disorder associated with aging. There are currently no effective treatments for AD. Bazhu decoction (BZD), a traditional Chinese medicine (TCM) formula, has been employed clinically to alleviate AD. However, the underlying molecular mechanisms are still unclear. Here we found that middle- and high-doses of BZD ameliorated the behavioral aspects of 5xFAD transgenic mice in elevated plus maze, Y maze and Morris water maze tests. Moreover, BZD reduced the protein levels of BACE1 and PS1, resulting in a reduction of Aβ plaques. We also identified a beneficial effect of BZD on oxidative stress by attenuating MDA levels and SOD activity in the brains of 5xFAD mice. Together, these results indicate that BZD produces a dose-dependent positive effect on 5xFAD transgenic mouse model by decreasing APP processing and Aβ plaques, and by ameliorating oxidative damage. BZD may play a protective role in the cognitive and anxiety impairments and may be a complementary therapeutic option for AD.

In this paper, the buffer-constrained throughput performance of a multi-user wireless-powered communication (WPC) system is investigated, where energy harvesting follows a non-linear model. The investigation focuses on the buffer overflow performance of sending data in the downlink (DL) from the access point (AP) node to each user equipment (UE) node and that in the uplink from each UE node to the AP node, based on which the throughput performance on both directions when a buffer constraint is enforced is studied. Specifically, the buffer overflow probability at each node is analyzed, based on which the buffer-constrained throughput is studied. In addition, to ensure the throughput performance under the buffer constraint, the DL transmission power allocation policy and the required energy storage capacity at each UE are investigated. Also, the optimal channel time allocation policy is studied with the objective of maximizing the minimum buffer-constrained throughput guaranteed to each UE at the same time. To this aim, an optimization problem is first formulated and then a dichotomy-based time allocation algorithm combined with a one-dimensional search is proposed to solve this problem. The analysis and results, explicitly relating the throughput to the buffer constraint in addition to WPC characteristics, shed new light on the design and performance analysis of WPC systems. © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Random network coding (RNC) has emerged as a promising technology. In this paper, we seek to answer the question that how RNC benefits cellular systems. A novel RNC-based space–time code (STC) scheme is proposed for the data transmission in MIMO system. In this scheme, RNC is integrated with the STC design for MIMO system. And then, the improved diversity order and multiplexing gain of the RNC-based STC scheme are analyzed and derived. This RNC-based STC scheme can also have benefit of RNC on some practical applications. After that, a general RNC-based STC protocol which describes the data transmission flow in practical system is designed for MIMO transmission. Finally, the performance of RNC-based STC scheme is evaluated through both link-level and system-level simulations. The simulation results show that RNC can provide extra diversity gain, multiplexing gain, or reduce the decoding complexity, and improve the bandwidth efficiency and user fairness in cellular system with MIMO.

Compared to the conventional human-to-human devices, the Internet of Things (IoT) devices needs fewer resources and lower power for data transmissions. As a result, how to increase the resource utilization efficiency and energy efficiency simultaneously is worth studying while enabling different types of IoT devices access to the future 5G networks. In this paper, we study a distance-based algorithm for resource allocation in a Further Enhancement to Device-to-Device (FeD2D) network. Firstly, an appropriate distance for resource reuse is found out to decrease the co-channel interference (CCI) between different relay user equipments (UEs). Then, more direct communications are processed in one subframe to improve the energy and resource utilization efficiencies in the proposed algorithm based on reuse condition. Simulation results verify the advantage of the proposed algorithm in power saving and full use of resources.

In this paper, we investigate the designation of transmission time intervals (TTls) in a LAA system. With considerations of backward compatibility and feasibility, two shortened TTI schemes are proposed to increase the flexibility of frame structure in the unlicensed spectrum. Additionally, the advantage of the designed shortened TTI schemes on the DL transmission performance is also studied for different cases of packet size. More specially, it is found that the system using the proposed shortened TTI schemes is able to reach the start point of a transmission more quickly when sending small packets. Therefore, the performance of small packets can be improved. Differently, the proposed shortened TTI schemes are able to reduce the padding time when transmitting large packets, so that the performance, especially the utilization of the maximum channel occupancy time (MCOT), can be improved. The simulation results verify that remarkable performance gain can be achieved under the proposed shortened TTI schemes. In addition, based on the analysis in this paper, it is suggested that shortened TTI should be included in the future designation of LAA systems in order to achieve better performance.

In this paper, we investigate the delay and delay-constrained throughput performance of a point-to-point wireless-powered communication system, where one node, e.g. a user equipment (UE), is powered by the wireless energy transferred from the other node, e.g. an access point (AP), and uses the harvested wireless energy to send data to the other node. Our focus is on the delay performance of sending data over the uplink from the UE node to the AP node, and on its throughput performance when a delay constraint is enforced. Two representative time allocation schemes in using the link for the AP node to transfer energy (maybe together with data) and for the UE node to send data are considered. In particular, a lower bound on the cumulative capacity of the uplink is derived. In addition, an upper bound on the delay distribution is obtained for stochastic traffic arrivals, based on which, the delay-constrained throughput performance is further analyzed. Moreover, the accuracy of the analysis is validated by comparison with extensive simulation results. The analysis and results shed new light on the performance of such a wireless-powered communication system. © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

In this paper, the delay and delay-constrained throughput performance of a point-to-point wireless-powered communication system is investigated. In this system, the wireless-powered node, e.g., a user equipment (UE), receives data at the same time when powered from the other node, e.g., an access point (AP), and uses the harvested wireless energy to send data to the other node. The investigation focuses on the delay performance of sending data in the downlink (DL) from the AP node to the UE node and that in the uplink (UL) from the UE node to the AP node, based on which the throughput performance on both directions when delay constraints are enforced is also studied. To this aim, the cumulative service capacity of the service process is first analyzed for both DL and UL, taking into consideration the delay caused by the nontransmission phase for the AP or UE in each charging cycle. Thereafter, a general upper bound on the delay distribution for stochastic traffic arrivals is obtained for both DL and UL, based on which the delay-constrained throughput performance is further studied. In addition, to ensure the delay performance, the required energy storage capacity and wireless charging rate are investigated. The obtained results are exemplified with two specific traffic types, and the accuracy of the analysis is validated by comparison with extensive simulation results. The analysis and results shed new light on the performance of wireless-powered communication systems. 2017 IEEE. Open Access.

Offloading the LTE data services to unlicensed spectrum has been considered by 3GPP in Release 13, which is defined as LAA (Licensed-Assisted Access). Unlicensed band is attractive because of its large amount of spectrum resource. However, coexisting with wireless devices already existing in unlicensed spectrum (such as Wi-Fi) is a primary issue be solved effectively. This paper proposed two dynamic max TxOP (transmission opportunity) algorithms based on Q-learning and expected capacity while inheriting the application of LBT(Listen-before-Talk), CCA-ED(channel clear assessment-energy detection) and discontinuous transmission. Using this framework, both LTE and Wi-Fi adjust the maximum occupancy time based on current traffic load or expected capacity dynamically, in order to improve the two systems' performance by configuring the transmission opportunity more reasonablely. Simulation results also show that the proposed approaches can enhance throughput and fairness significantly under both low and high traffic load, proving that the proposed dynamic TxOP algorithms offer new possibilities for better coexistence performance in LAA system.

In this paper, a spectrum sharing scheme adapted for the operation of Long Term Evolution (LTE) in unlicensed band (LTE-U) and WiFi system is proposed. This scheme optimizes the resource in unlicensed band based on decision tree learning and repeated game. We consider a flexible architecture decoupling control plane from data plane in the coexistence system. In control plane, strong ability of data processing is provided. Controllers learn the latest data set in the pool to build decision trees. According to the decision tree, controllers deduce the network status of the opponent. Repeated game is played to share spectrum resources for maximizing the resource utilization in the coexistence system. At the beginning of each game stage, controllers use decision tree to make informed decisions quickly. In repeated game, an encouragement mechanism is proposed to stimulate operators to share spectrum resources. Simulation results show that dynamic spectrum sharing is able to improve throughput and spectrum efficiency in unlicensed band. At the same time, this scheme also balances the traffic load and guarantees fairness among multiple systems.

With the development of smart phones, one of the hot research topics for wireless personal communication technologies has begun to transit from reaching higher communication capabilities to better Quality of Experiences (QoE). However, for streaming services, such as online music or online video, which is one of the mainstream services in the future wireless network, there is still no breakthrough optimization beyond the Quality of Service (QoS) hence the optimization results are not satisfactory. Based on our study, this problem could be relieved by altering the criterion of wireless resource allocation from enhancing users' QoS to enhancing their QoE, which specifically means that the scope of the research is extended from the so-called last mile between the network and the user equipment to the last few inches between the user equipment and the user himself. Unfortunately, it seems that all current QoE researches are still not jointly considering the users' environment and user equipments' performance, both of which are paramount factors of the last inches that will influence users' QoE directly and profoundly. Hence, in this paper, we propose a QoE model involving the environment and equipment factors, and then we use this model to guide the wireless resource allocation. Simulation results show that this resource allocation method will increase the effectiveness of network resource utilization as well as improve the average of satisfaction of users.

Cognitive radio has become a promising technology to increase spectrum utilization through spectrum sharing between licensed users (primary users) and unlicensed users (secondary users). Performance evaluation and analysis is of key importance to get more knowledge of this newly emerged technology.Queueing theory and Markov chain model have been applied to conduct the analysis, where some results are obtained. The existing research sheds light on the performance of cognitive radio networks. However, there are also some limitations. Poisson arrival and exponentially distributed service time are mostly assumed in existing analysis. With these assumptions, existing queueing theory results, particularly M/G/1 priority queue results, can be directly applied, and the Markov chain model can be established. However, these assumptions are too restrictive for modern wireless communication networks, where the traffic can be of different types and the channel capacity can vary over time. In addition, particular focus is made on average values (such as average delay) with little investigation on probabilistic distribution bounds.Therefore, new methodology is needed to make a breakthrough and to bring new insights regarding performance of cognitive radio networks. Network calculus, a newly developed theory, provides a possible solution. It was firstly proposed by R. L. Cruz in 1991, and has involuted into two branches now, i.e., deterministic network calculus and stochastic network calculus. There are two basic concepts in network calculus: (stochastic) arrival curve and (stochastic) service curve, which are used to describe the arrival process of input traffic and the service process of server, respectively. Probabilistic performance guarantees can be analyzed using stochastic network calculus. In addition, the independence between arrival process and service process can be exploited to obtain tighter probabilistic bounds, which is called as independent case analysis.This work is devoted to applying network calculus analysis, particularly stochastic network calculus, to performance evaluation of a cognitive radio network. Generally, this work contains two scenarios: a single-channel scenario and a multiple-channel scenario.In the single-channel scenario, several key factors are considered and discussed. Different traffic models, including Periodical source and (Compound) Poisson source, are considered. The sensing error process, which can be further divided into mis-detection process and false alarm process, is modeled, and the corresponding stochastic arrival process is analyzed. Both constant channel and Gilbert-Elliott ON-OFF fading channel are investigated, and the stochastic service curves are obtained. In addition, the influence of different re-transmission schemes is also studied. These schemes include no-re-transmission, re-transmission until success and maximum-Ntime re-transmission. Probabilistic delay distribution bound and probabilistic backlog distribution bound are obtained and discussed. Furthermore, delay-constrained capacity is defined and capacity regions for both primary users and secondary users are also studied. Independent case analysis is applied in some cases, and results are compared and discussed. In the multiple-channel scenario, the main concern is put on the guaranteed service of multiple parallel channels and delay-constrained capacity by assuming perfect sensing and constant channel.In validating the theoretical results, system configurations are specified mainly based on Long Term Evolution (LTE) networks, and numerical calculations executed in Matlab are made to visually depict the results. Simulation platform by C++ language is also constructed to obtain simulation results. Related results show the influence of different schemes or parameters on system performance and capacity region. Comparison between the numerical and simulation results is made, which further verifies the theoretical deductions.

Astrocyte dysfunction and inflammation are associated with the pathogenesis of major depressive disorder (MDD). However, the mechanisms underlying these effects remain largely unknown. Here, we found that multiple endocrine neoplasia type 1 (Men1; protein: menin) expression is attenuated in the brain of mice exposed to CUMS (chronic unpredictable mild stress) or lipopolysaccharide. Astrocyte-specific reduction of Men1 (GcKO) led to depressive-like behaviors in mice. We observed enhanced NF-κB activation and IL-1β production with menin deficiency in astrocytes, where depressive-like behaviors in GcKO mice were restored by NF-κB inhibitor or IL-1β receptor antagonist. Importantly, we identified a SNP, rs375804228, in human MEN1, where G503D substitution is associated with a higher risk of MDD onset. G503D substitution abolished menin-p65 interactions, thereby enhancing NF-κB activation and IL-1β production. Our results reveal a distinct astroglial role for menin in regulating neuroinflammation in depression, indicating that menin may be an attractive therapeutic target in MDD.

System-level simulation has been widely used to evaluate system performance. Simulation methodologies have also been comprehensively discussed in different organizations or institutions. Most of the simulation methodologies proposed, however, mainly focus on one area of specific technologies. How to evaluate the performance of multiple air interface systems (e.g., cdma2000, WCDMA, WiMAX, and their evolutions) in a fair and comprehensive manner has not been addressed extensively. This article presents a unified simulation methodology, including fading channel models, system configurations, and how to consider technology-dependent algorithms such as scheduling, overhead modeling, interference margin definition, and resource allocation based on system loading. This article uses this framework to compare three major existing radio technologies: cdma2000 1x EV-DO Rev. A, WCDMA HSPA, and mobile WiMAX based on 802.16e. Key simulation results based on our suggested system models and settings are presented and analyzed. It is shown that under our unified framework, the two CDMA systems exhibit higher spectrum efficiency than mobile WiMAX, especially on the downlink, while mobile WiMAX provides a higher peak rate.

In this work, we propose a stochastic network calculus based approach to study the packet delay in a multichannel network comprising one control channel and multiple parallel data channels. A node should compete with other nodes on the control channel before it is allowed to transmit packets on the data channels. The packet delay is the sum of packet (or node) competition delay, queueing delay and transmission delay. We derive an upper bound of the CCDF (complementary cumulative distribution function) of the packet delay, which is also called the probabilistic delay bound, in a general multi-channel network where not only the stochastic traffic can be any type, but also the above three types of delay can either be independent or correlated. Moreover, for further understanding and applying the proposed approach, we also employed Poisson traffic as a specific case to investigate the impact factors on the packet delay through traffic characteristics and network configurations.

Energy evaluation of wireless transmission for data service under different QoS (quality of service) constraints is a hot topic in green communications. In this paper, we employ the theory of the stochastic network calculus to investigate the relationship between the traffic arrival rate and energy harvesting rate under the delay and energy storage constraints. We first construct a wireless system model which works only by consuming the harvested renewable energy. Also, stochastic traffic arrivals, packet size as well as a two-state Markov chain interference on energy harvesting are jointly considered to ensure the accuracy of the analysis. We derive the minimum energy harvesting rate needed to satisfy the delay and energy storage constraints under a given average arrival rate. The efficiency of the harvested energy is also studied and shown to be convex in the numerical simulation. Numerical results illustrate that while the minimum energy harvesting rate is positively correlated with the packet size, it is negatively related to the delay requirement, under a given arrival rate. Additionally, the probabilistic bound of energy insufficiency is shown to be positively correlated with the transition cycle of the interference.

Ultra-dense Small Cell deployment is a sensible design of heterogeneous network, which provides a good performance of hot spots coverage enhancement and traffic load balancing. The growing energy consumption pressure becomes one of the main challenges of the Small Cell application. Cloud Radio Access Network (C-RAN) can promise significant energy consumption savings for Small Cells via the separation between RRH and BBU. In this paper, we propose a novel software defined C-RAN (SDC-RAN) architecture in Small Cell network. Moreover, a self-adaptive power adjustment scheme (SA-PAS) is introduced, considering the influence of users' current and history traffic demands during downlink power allocation. The goals are to strike a good balance between energy efficiency and user experience. Simulation results show that the expected system throughput can be achieved with limited resource consumption in SDC-RAN based on Small Cell deployment.

A sensible design of ultra-dense Small Cell network involves striking a good balance between energy efficiency and user experience especially in hot spots. In this paper, we propose a self-organized resource allocation scheme (SO-RAS) as an enhanced solution for the system performance, which can coordinate resource allocation within Small Cell clusters based on the self-organized mechanism. We take the users' access distribution as a constraint weight when conducting downlink cooperative power adjustment, aiming to adapt system resource consumption corresponding with the current traffic load. Simulation results show that the proposed strategy improves system performance in hot-spot users' throughput and can contribute to the system energy efficiency ratio in ultra-dense networks.

The dynamic uplink-downlink reconfiguration of TD- LTE is regarded as an effective method to increase the resource efficiency and optimize the system performance. With different transmission directions and the dense deployment of small cells in the heterogeneous network, the interference situation becomes complex and critical in both uplink and downlink, especially for the cell-edge UE. In this paper, we discuss the interference coordination and mitigation problem in the dynamic TDD network. With cell-clustering interference mitigation, the synchronous operation can be provided in a cluster and well isolation can be obtained between cells in the different clusters. Furthermore, we propose that the simplified downlink CoMP DCS mode can be used in the clusters to optimize the downlink performance. At last of the paper, we analyze the performance gain of the proposed scheme by system level simulation. The results show that both uplink and downlink performance for the cell-edge UE are improved.

Performance gain can be obtained by dynamically reconfiguring the uplink and downlink radio frames in TDD systems. FDD systems can also benefit from the flexibility in the allocation of uplink and downlink resources. The paper proposes a specific implement of flexible duplex based on selection between different designs of radio frames to make the FDD network more adaptive to the real time situation of uplink and downlink traffic. The interference generated by flexible duplex is analyzed with a typical mathematic model and several scenarios are discussed to find out the ideal scenario to apply flexible duplex. Some simulation results are given to show the gain obtained by the scheme.

The green communication draws a lot of attention in recent years. Meanwhile, as a promising technology, cognitive radio will constitute an important part of the future communication networks. Energy consumption of cognitive radio network is worthy studying, which is analyzed in this paper applying stochastic network calculus. A multi-channel cognitive radio network model is introduced. Stochastic network calculus is then used in the analysis, which is a newly developed theory dealing with queuing system found in computer networks. Guaranteed service for secondary users is firstly derived, followed by stochastic service curve derivation. Then, minimum transmission rate is conducted which is an important variable in energy analysis. After that, relationship between energy consumption and transmission rate is presented. As part of the derivation, delay bound and transmission power are discussed. Finally, numerical results of transmission rate, transmission power and energy consumption are shown for different constraint, where the influence of channel quantity is further discussed.

Dynamic uplink and downlink reconfiguration is studied as an effective method to improve the system packet throughput performance in the LTE Heterogeneous Network. There are various kinds of traffic with different quality of service requirements in the practical wireless network, which has not been fully considered by the existing resource allocation strategies for dynamic TDD. In this paper, a resource allocation scheme coordinating the time and frequency resource for mixed traffic in the dynamic TDD scenario is proposed, which can guarantee the system requirements, such as time delay budget, packet drop rate and packet throughput. Utilities of users with different services are considered in the scheduling and dynamic UL-DL reconfiguration. Theoretical analysis and system level simulation are carried out to evaluate the performance. The simulation results show that compared with the existing resource allocation schemes, the proposed one offers a better performance, which are low packet drop rate of VoIP users and high packet throughput of FTP users. like best effort (BE) data traffic without delay requirement. The other one is real-time (RT) services with QoS requirements about packet drop rate and packet delay, such as VoIP or video service. It's of great significance to consider differences of the mixed traffic to avoid the waste of resource and improve users' experience. There have been several algorithms for the dynamic uplink- downlink resource allocation. In (2), the amount of UL/DL data to be transmitted in the buffer is calculated for reconfiguration. In (3), the reconfiguration is based on the UL and DL data currently in the buffer and considers the impact of historical traffic data, while full bandwidth scheduling with simple First-in-First-out (FIFO) rule is used for frequency resource allocation. The spectral efficiency of UL or DL is also taken into account, and latency-based proportional fair (PF) scheduler is used (4). However, these algorithms only deal with certain traffic model without consideration of the quality of service (QoS) requirement. The QoS aware reconfiguration method for mixed traffic is proposed in (5), but the FIFO

Small cell enhancement has been considered as a promising way to cope with the rapid growth of need in mobile data traffic. However, it also leads to severe inter-cell interference, which means that some interference mitigation scheme is indispensable. Among lots of interference mitigation scheme, small cell on/off adaptation is thought to be an effective one. In this paper, small cells are modeled as a 2-D Poisson point process (PPP) based on stochastic geometry. And then the coverage probability of the small cell network can be derived as a tractable close-form expression. In addition, a Monte Carlo simulation is performed to verify the accuracy of the stochastic geometry model. Subsequently, the numerical results shows that small cell on/off adaptation can improve the receiving signal to interference plus noise ratio (SINR) of small cell downlink transmission by 4–6 dB. Meanwhile, the average ergodic transmission rate and power efficiency are both enhanced due to the improvement of the wireless environment.

Relay-assisted Device-to-Device (D2D) communication is an enhanced technology for D2D communication. With relay nodes' assistances, the communication distance of the D2D pair is extended and the quality of communication can be improved. This paper focuses on the achievable transmission capacity of relay-assisted D2D network while keeping a low outage probability of the cellular users. based on stochastic geometry, the mathematical model of relay-assisted D2D network, with relay selection criterion, is formed and analyzed. Subsequently, the optimal transmission power ratio of the cellular system to the D2D system and the optimal relay selection range are derived. Furthermore, the achievable transmission capacity with derived optimal parameters is presented as a close-form expression. Then the numerical results show that the performance of the D2D network can be improved by relay-assisted transmission in case of poor wireless environment. In addition, the influences of the densities of both cellular, D2D and relay users and the communication distances between D2D pairs are evaluated in this paper.

The dynamic adjustment of TDD UL-DL configuration based on the instantaneous traffic conditions can be an effective way to optimize the system performance. Small cells in LTE heterogeneous network are considered to be one of the candidates for the dynamic adjustment. In this paper, we focus on UL-DL reconfiguration algorithms to conduct the dynamic adjustment, where the QoS requirement differences of mixed services are considered. Unlike the previous algorithms, we develop a UL-DL reconfiguration algorithm which is aware of traffic QoS requirement and guarantees both packet bit rate and packet delay. The performance improvement is theoretically analyzed and simulated on system level. Simulation results show that the proposed algorithm outperforms the existing dynamic UL-DL reconfiguration algorithms in terms of packet delay and packet drop ratio.

The conflict between energy consumption and battery capacity has become more significant in modern mobile terminals that support various functions in addition to traditional voice. It is of great importance to extend battery lifespan and at the same time to guarantee the required quality of service (QoS). In this paper, we investigate the relationship between the battery lifespan of a mobile terminal and the data traffic on the terminal that has a delay constraint. Specifically, an uplink with periodical traffic arrival and Rayleigh fading channel is considered. An optimization problem is formulated with the objective of minimizing the transmission rate while at the same time ensuring the required delay guarantee, so that the battery lifespan can be maximized. Numerical results under different configurations are presented and discussed.

Recently, the evaluation on quality of the air interface in a wireless network has shifted from emphasis on QoS (quality of service) only to incorporation of QoE (quality of experience). However, it seems that QoE metrics have not been related to the surroundings of the served users so far, which may have a great influence on users' expected QoE. For instance, with a high level of QoS, a user's expectation of QoE could still be terrible because of the serious interference from the surroundings such as noise, ambient light or shaking of terminals due to mobility. From another perspective, it means that in such a case a high level of QoS may be helpless to enhance users' QoE and the requirement could be relaxed accordingly. In this paper, an approach called surrounding-adaptive QoE adjustment (SAQA) is proposed to optimize the capacity and the quality of air interface with voice service as an example. The basic idea of the approach is that user equipment (UE) detects the surroundings interference which may impact users' QoE and then adjusts QoS according to the detected results: a lower level of QoS is chosen in a bad environment to enhance the capacity, while a higher level of QoS is selected to guarantee the users' QoE in a better circumstance. Simulation results show that this method can remarkably enhance the voice capacity of the communication systems as well as guarantee users' QoE.

In this paper, we consider a multi-channel cognitive radio system serving a primary network and a secondary network, and analyze the quality of service and delay-constrained capacity of the secondary network. Specifically, by assuming that a certain amount of resource is exclusively reserved and used on each channel by the primary network, we derive the traffic transportation capacity that is guaranteed to the secondary network. Based on this, we analyze the traffic delay distribution in the secondary network and derive an upper bound on it, which allows us to further obtain a guaranteed capacity of the secondary network in serving traffic with probabilistic delay requirement. Both numerical and simulation results are presented for an example where the secondary network traffic follows a model taken from 3GPP LTE. The delay distribution, average delay and delay-constrained capacity of the secondary network are compared. The excellent match between analytical results and simulation results validates the theoretical analysis.

Part 1: - PE-CRN 2011 Workshop; International audience; In this paper, performance evaluation of a cognitive radio network is conducted. The analysis is based on stochastic network calculus. The system is supposed to work in a Time Division Multiple Access(TDMA) mode with fixed slot length. The wireless channel is modeled as a Gilbert-Elliott (GE) fading channel, where the channel quality transits between state ON and state OFF according to a Markov chain. Spectrum sensing errors, which can be classified into mis-detection and false-alarm, are taken into consideration. Particularly, a stochastic arrival curve for spectrum sensing error process, and a stochastic service curve for GE channel, are derived. In addition, performance distribution bounds are obtained based on stochastic network calculus. Furthermore, numerical calculations are made to show the capacity limits under delay constraints.

In this paper, we use stochastic network calculus to analyze a cognitive radio network, where influences of imperfect spectrum sensing and different retransmission schemes are considered. In particular, stochastic arrival curves for spectrum sensing error processes are derived firstly, based on which stochastic service curve for each class of users is obtained under different retransmission schemes, including without retransmission, retransmission until success and maximum-N-times retransmission. Then backlog and delay bounds for primary and secondary users are derived. Finally, numerical results are shown for different types of traffic, where the influence of different retransmission schemes is further discussed.

Cooperative spectrum sensing, a key technology in cognitive radio, has to summarize all the detection information from cognitive terminals without licensed band. In order to employ both reliable and efficient transmission of overhead, this paper seeks a way of quantifying the detection information with variable length to save the spectrum resource as much as possible. Analysis and simulation show the detection performance of our scheme is similar to the optimal linear combination scheme and much higher than the “OR” combination one, and even the total overhead does not increase significantly than the “OR” combination scheme.

In this paper, we first model the proposed solutions to electronic serial number (ESN) exhaustion issue. Then we evaluate performance of reusing ESN and using pseudo ESN which are the proposed solutions in code division multiple access (CDMA) system when ESN allocation issue is referred to. System model based on four assumptions is detailed described, and then collision probabilities are analyzed from three different aspects: individual user aspect, certain cell aspect and whole system aspect. During the procedure of modeling and analysis, probability theory is adopted when needed. At last, numerical results are given out which can be used as a guideline for solution of ESN exhaustion problem.