A distributed power allocation scheme was presented to maximize the system capacity in dense small cell networks. A new signaling called inter-cell-signal to interference plus noise ratio (ISINR) as well as its modification was defined to show the algebraic properties of the system capacity. With the help of ISINR, we have an easy way to identify the local monotonicity of the system capacity. Then on each subchannel in iteration, we divide the small cell evolved node B’s (SeNBs) into different subsets. For the first subset, the sum rate is convex with respect to the power domain and the power optimally was allocated. On the other hand, for the second subset, the sum rate is monotone decreasing and the SeNBs would abandon the subchannel in this iteration. The two strategies are applied iteratively to improve the system capacity. Simulations show that the proposed scheme can achieve much larger system capacity than the conventional ones. The scheme can achieve a promising tradeoff between performance and signaling overhead.

Focusing on the load balancing problem among multi-cells in long term evolution (LTE) networks with mixed users, a new multi-objective optimization modeling strategy, which integrates the guaranteed bit rate (GBR) and the best effort (BE) users, was proposed. In consideration of quality of service (QoS) priorities of different users, a decomposition method was presented to solve the original model. Derivations such as applying Lagrange multiplier method, sub-optimal solutions for mixed users were deduced. Based on derived solutions, including resource allocation schemes, a practical multi-objective load balancing algorithm jointly dealing with mixed users was given. Simulation shows a significant improvement of GBR users’ satisfaction level and BE users’ throughput in LTE networks by using the proposed algorithm.

As known that the effective capacity theory offers a methodology for exploring the performance limits in delay constrained wireless networks, this article considered a spectrum sharing cognitive radio (CR) system in which CR users may access the spectrum allocated to primary users (PUs). Particularly, the channel between the CR transmitter (CR-T) and the primary receiver and the channel between the CR-T and the CR receiver (CR-R) may undergo different fading types and arbitrary link power gains. This is referred to as asymmetric fading. The authors investigated the capacity gains achievable under a given delay quality-of-service (QoS) constraint in asymmetric fading channels. The closed-form expression for the effective capacity under an average received interference power constraint is obtained. The main results indicate that the effective capacity is sensitive to the fading types and link power gains. The fading parameters of the interference channel play a vital role in effective capacity for the looser delay constraints. However, the fading parameters of the CR channel play a decisive role in effective capacity for the more stringent delay constraints. Also, the impact of multiple PUs on the capacity gains under delay constraints has also been explored.

This paper focuses on the energy efficiency of cognitive relay (CR) networks with cooperative sensing, joint optimization of the sensing time and the signal-to-noise ratio (SNR) is studied to maximize the energy efficiency of CR network. Theoretical analysis shows that there exists an optimal sensing time and optimal SNR to make the energy efficiency maximized under a constraint of detection probability. Simulation results illustrate that the optimal fusion rule performs better than the OR rule and the AND rule in terms of the energy efficiency. By properly designing the fusion rule threshold as well as the number of cooperative sensing users, the energy efficiency of CR networks can be further improved.

Energy efficiency (EE) can be enhanced by retransmissions and combining in hybrid automatic repeat request (HARQ) system. However, it is difficult to optimize the transmit power of each retransmission when the accurate retransmission number and future channel state information (CSI) cannot be obtained. This paper proposes a simple energy efficient HARQ scheme for point-to-point wireless communication. In the proposed scheme, the conditional word error rate (WER) of each retransmission is fixed and the transmit power is adapted correspondingly. Three performance metrics are analyzed including average transmission number, throughput and EE. Compared with the conventional equal power HARQ scheme, the proposed scheme can significantly improve the EE and other two metrics under the same constraint of average transmit power or average energy consumption. Furthermore, it is found that, selecting a conditional WER which is slightly smaller than the optimal one is sufficient for practical implementation.

Due to its large bandwidth and the complexity of indoor environment, the UWB channel is frequency selective, which affects the data rate and reliability of UWB communi- cation. This paper proposes an amplify-forward relay scheme to mitigate this reliability problem. The relay can be used to acquire capacity gain and diversity gain just like MIMO. The first investigation focuses on the relay-node selection criterion and combination ration for capacity gain. Capacity gain depends on the correlation of frequency responses between direct link and relay link in addition to relay link SNR. Increased similarity of the two frequency responses increases capacity gain. Capacity gain’s best relay and combination ratio are found by taking the derivative of the capacity equation. Solution of the quadratic derivative equation of ratio finds the optimal ratios for every potential relay node. The second investigation focuses on relay- node selection criterion and combination ratio for diversity gain respectively.Higher diversity gain corresponds to less-deep-faded subchannels of combined signal. Reduced computation divides the problem into two steps: The first step selects the relay node according to the criterion that is dependent on the average of SNR(f) and variance of SNR(f) . The second step solves the combination ratio-optimization problem for optimal ratio. Numerical simulation shows that our scheme is effective in pursuit of capacity gain and of diversity gain.

In this paper, we propose a model based on dynamics equation for performance analysis and optimization for heterogeneous wireless networks (HWNs). First, the channel occupation state with time of HWNs is modelled by dynamics equation, in which users’ mobility as an important factor affecting system performance is considered. Then the steady state probability distribution of channel occupation is derived. Based on the results, the expression of the throughput of HWNs is deduced, which includes a factor ρ which is the ratio of service arrival rate accessing one of the networks to the total service arrival rate in the overlapping area. And this paper proposes to maximize the throughput of the HWNs by optimizing the factor ρ to efficiently utilize the resources. Simulation results show that the proposed optimization method can effectively improve the throughput and in the meanwhile decrease the blocking probability of the whole system.

This paper proposes a hybrid scheme of the Alamouti coding and vertical bell labs layered space-time (V-BLAST) with the zero-forcing (ZF) receiver, which can achieve the unequal error protection (UEP) transmission in terms of the differences of importance in the layered sources. We analyze the tradeoff between spatial diversity and multiplexing in a mathematical manner, and prove the monotonic behavior of the crosspoint. Based on this scheme, we adopt V-BLAST to provide high data rates for the enhancement layer (EL) bitstreams, and adopt Alamouti coding to guarantee high reliability for the base layer (BL) bitstreams. Meanwhile, to improve the transmission reliability for the layered sources under the multiple-input multiple-output (MIMO) system with the limited-bandwidth and the total limited power, and to raise the frequency bandwidth efficiency, we take the power allocation considered in this proposed scheme. The simulation results show that the hybrid scheme has the average 1.9 dB and 1.3 dB gain in video peak signal-to-noise ratio (PSNR), compared with the pure spatial diversity and pure spatial multiplexing scheme, respectively.

Because of the integration of long term evolution (LTE) technology and mobile satellite communication systems, uplink access technology for LTE-based geo-stationary earth orbit (GEO) satellite has become a popular research topic for satellite system. In order to solve the problem of unreasonable design for physical random access channel (PRACH) signal structure and reduce the effect of time uncertainty, this paper proposes a novel random access preamble based on time pre-compensation (TPC) for LTE-Satellite (LTE-S) system. In this scheme, by applying the method of non-linear least squares, the user terminal (UT) can use the receiving power to estimate the communication round trip delay (RTD) and based on the transmission delay of the beam center and the satellite, RTD can be compensated before transmission. Therefore, the preamble length and duration can be reduced without related to the maximum of RTD. In order to verify the performance of the scheme, the MATLAB is used to build a test system. The simulation results show that the proposed preamble satisfies the requirements of LTE-S system, and the better performance than previous researches is obtained.

Since the different characteristics of various network services determine that their requirements for network are also disparate, the performance of one network varies according to the services running on it. However, most of previous network performance evaluation (NPE) researches conduct evaluations based on the network parameters, but without considering from the perspective of specific service running on the network. In view of this issue, a novel service-oriented NPE framework is proposed. First, the characteristics discrepancy among different types of services are investigated. Next, in order to conduct comprehensive evaluation of multiple services, an enhanced low-complexity adaptive (LA)-fuzzy analytical hierarchy process (FAHP) is introduced; meanwhile by applying the experts-construct-directly (ECD) algorithm proposed later, the consistency check required in previous studies can be omitted, thereby significantly reducing the computation complexity and assessment workload for experts. Then, in accordance with the features of each service, corrections are made to their respective membership functions, thus making the proposed LA-FAHP adaptive to various service evaluation scenarios. The subsequent comparison with other NPE methods well proves the effectiveness and high sensitivity of proposed framework, and the analysis verifies the low computation complexity of the proposed algorithms as well.

Hybrid cloud peer to peer (P2P) system is widely used for content distribution by utilizing user’s capabilities to relieve the cloud bandwidth pressure. However, as demands for large-size files grow rapidly, it is a challenge to support high speed downloading experience simultaneously in different swarms with limited cloud bandwidth resource in such system. Therefore, it requires an optimized cloud bandwidth allocation to improve overall downloading experience of users. In this paper, we propose a system performance model which characterizes the relationship between cloud uploading bandwidth and user download speed. Based on the model, we study the cloud uploading bandwidth allocation, with the goal of optimizing user’s quality of experience (QoE) that mainly depends on downloading rate of desired contents. Furthermore, to decrease the computation complexity, we put forward a heuristic algorithm to approximate the optimized solution. Simulation results show that our heuristic algorithm can obtain higher user’s QoE as compared with two typical bandwidth allocation algorithms.

An adaptive quantum-inspired evolutionary algorithm based on Hamming distance (HD-QEA) was presented to optimize the network coding resources in multicast networks. In the HD-QEA, the diversity among individuals was taken into consideration, and a suitable rotation angle step (RAS) was assigned to each individual according to the Hamming distance. Performance comparisons were conducted among the HD-QEA, a basic quantum-inspired evolutionary algorithm (QEA) and an individual’s fitness based adaptive QEA. A solid demonstration was provided that the proposed HD-QEA is better than the other two algorithms in terms of the convergence speed and the global optimization capability when they are employed to optimize the network coding resources in multicast networks.

This paper proposes a novel method, primarily based on the fuzzy adaptive resonance theory (ART) neural network with forgetting procedure, for moving object detection and background modeling in natural scenes. With the ability, inheriting from the ART neural network, of extracting patterns from arbitrary sequences, the background model based on the proposed method can learn new scenes quickly and accurately. To guarantee that a long-life model can derived from the proposed mothed, a forgetting procedure is employed to find the neuron that needs to be discarded and reconstructed, and the finding procedure is based on a neural network which can find the extreme value quickly. The results of a suite of quantitative and qualitative experiments conducted verify that for processes of modeling background and detecting moving objects our method is more effective than five other proven methods with which it is compared.

In distributed cognitive radio (CR) network, the cooperative spectrum situation sensing based on consensus scheme may be disrupted by spectrum sensing data falsification (SSDF) attacks. In this paper, a secure spectrum situation fusion scheme based on reputation is proposed to counter attacks. The neighboring nodes of secondary users (SUs) get the corresponding dynamic trust value according to their behavior, which restrict the impact of the malicious behavior on the premise to ensure information interaction of normal nodes. Theoretical analysis and simulation results show that the consensus fusion scheme based on reputation has better performance than the existing algorithm which eliminates the neighboring node with the biggest deviation value from mean value. It demonstrates that the proposed scheme not only achieves better convergence properties but also has higher detection probability than the existing scheme in the process of spectrum situation fusion.

A design of broadband dual-polarized antenna with low cross polarization and high isolation was presented. The antenna is composed of a cross dipole, a folded ground, two feeding networks, and a reflector. The impedance bandwidth was enhanced by utilizing the mutual coupling between the two dipoles. A kind of meandering folded Marchand balun was skillfully integrated on the support column of the antenna to excite the dipole differentially, which can deliver both balanced (within 0.5 dB) power splitting and consistent (±5°) phase shifting from 1.71 GHz to 2.17 GHz. The standing wave ratios (SWRs) of each port are less than 1.5. By using this feeding network, the antenna has good performance in isolation (> 45 dB) and cross polarization (> 30 dB) over the entire operating frequency band. Moreover, the gain (~8.6 dB) of the proposed antenna is stable with frequency and the antenna structure is very firm due to the support column. The proposed antenna can be easily formed an array for digital cellular system (DCS), personal communications service (PCS) and 3rd generation (3G) applications.