Volume 68, Issue 3-4

In this paper, we investigate the performance of a cooperative relay network over Rayleigh-Rician asymmetric fading channels, where a source transmits signals to a destination with the help of multiple fixed-gain amplify-and-forward (AF) relays. Specifically, we derive the closed-form expression for the moment generating function (MGF) of the output signal-to-noise ratio (SNR), and develop an approximate yet accurate method to evaluate the average symbol error rates (ASERs) of the network with respect to three widely used modulations, namely, M -PAM, M -PSK and M -QAM. Moreover, to gain further insights, we provide the asymptotic ASER expressions at high SNR, and thus obtain both of the diversity order and array gain. Finally, the validity of the analytical results is confirmed through some computer simulations.

Nowadays cognitive radio networks (CRNs) have been proposed as a promising method to solve the problem of radio spectrum shortage and spectrum sensing has been known as a key step to enable the CRNs and utilize the precious spectrum resource. In order to protect primary users from being interfered, most of the related works have focused on the restriction of the probability of missed detection only, however in practice, even under the missed detection cases, secondary users located far away from the primary users can also be interference-free to primary users. Motivated by this fact, in this paper we first introduce an interference-aware spectrum sensing model and investigate the issue of sensing-throughput tradeoff in interference-aware cognitive radio networks for a single detector. Then we extend the interference-aware spectrum sensing model to the problem of cooperative spectrum sensing among a group of secondary users. Specifically, in this paper we take the throughput as the objective of the cognitive radio network, and search for the maximum achievable throughput by jointly optimizing the sensing time and the detection threshold. Compared with the existing algorithms, the accompanying analytical and numerical analysis in this paper show that the proposed algorithm makes better utilization of the spectrum resource, for which a higher throughput performance can be achieved in cognitive radio networks.

Spectrum sensing is a key technical challenge for cognitive radio (CR). It is well known that multi-cycle cyclostationarity (MC) detector is a powerful method for spectrum sensing. However, conventional MC detector is difficult to implement due to its high computational complexity. This paper pays attention to the fact that the computation complexity can be reduced by simplifying the test statistic of conventional MC detector. Based on this simplification process, an improved MC detector is proposed. Compared with the conventional one, the proposed detector has the low-computational complexity and high-accuracy on sensing performance. Subsequently, the sensing performances are further investigated for the cases of Rayleigh, Nakagami-m, Rician and composite Rayleigh fading-shadowing channels. Furthermore, the square-law combining (SLC) is introduced to improve the detection capability in fading and shadowing environments. The corresponding closed-form expressions of average detection probability are derived for each case by the moment generation function (MGF) approach. Finally, illustrative and analytical results show that the efficiency and reliability of proposed detector and the improvement on sensing performance by SLC in fading and shadowing environments.

In this work an analysis of distortion range limited in Rayleigh and Nakagami channel interference was made. There were given analysis dependences abating planning process of compatible radio communication network.

This paper presents a new model of the CFAR (Constant False Alarm Rate) detector. Mentioned CFAR detector is named cell-averaging-trimmed-mean CFAR (CATMCFAR), which is a combination of cell-averaging CFAR and trimmed mean CFAR. It is implemented in the receiver of the software defined radar. Expressions for the probability of detection, the probability of false alarm and the average decision threshold are derived. The article presents detection of simulated radar targets in Weibull clutter and real radar targets in real clutter and compares characteristics of new CATM-CFAR with some realized well known CFAR detectors.

GSM network operators are required to free up some of the spectrum allocated for voice traffic in order to serve 3G and 4G users. Re-farming 900 MHz and 1800 MHz bands into HSPA, W-CDMA (UMTS) and LTE is a challenge faced by operators with growing GSM voice traffic as 3G systems require 5 MHz bandwidth which is 25 times more bandwidth than a typical GSM channel. 4G systems (LTE) may even use 10 MHz to show superiority over the 5 MHz 3G systems. It is required to cope with the GSM voice traffic with significantly less bandwidth in order to accommodate 3/4G users. Orthogonal Sub Channel (OSC) is a novel technique offering efficient hardware utilization that can result in doubling GSM voice capacity. This is achieved by allowing two users to share the same physical radio resources. OSC can be used in phasing-out GSM networks to release significant frequency spectrum for 3/4G users. In this work, a thorough analysis on OSC performance gain is presented. The hard capacity gain offered by OSC is calculated as a function of the OSC penetration and compared with system level simulations. It is shown that hard capacity can be maintained with less number of TRXs (transceivers), and consequently, narrower spectrum. This paves the way for re-farming the released GSM spectrum into 3/4G traffic.

Active cooperation is used to improve the security of wiretap channel. Especially, the number of relay antennas has an important effect on the security of wiretap channel. However, in previous work it is seldom comprehensively considered how to make full use of the relay antennas in the transmission process. In this paper, we investigate the influence of the number of relay antennas on the secure degrees of freedom (s.d.o.f.). We consider the situation that there is no direct link between the source and the destination. Firstly, we study the condition that the relay between the source and the destination adopts an amplify-and-forward (AF) strategy. Under this situation, the theoretic estimation is given to verify that the number of antennas at the relay have an influence on the s.d.o.f. in the case of N r  ≤ min{ N t ,  N d ,  N e } and N d  ≥  N e  ≥  N r  ≥  N t . Otherwise, it almost has no influence on the s.d.o.f. Meanwhile, if the relay adopts a decode-and-forward (DF) strategy. We can prove that if N e  ≤ ½( N t  +  N d ), the s.d.o.f. is ½ min( N r ,  N d ) and if ½( N t  +  N d ) <  N e  ≤  N d  + ½ N t , the s.d.o.f. is ½( N t  +  N d  − 2 N e  + min( N r ,  N d )). The simulation results are consistent with the theoretical results.

Energy efficiency is a crucial requirement for energy-aware ad hoc networks. The efficient relay management, i.e., the joint issue of relay node selection and transmit power control, can be applied to reduce and balance energy consumption. In most existing works, however, the nodes are required to share the distributed information, e.g., the channel knowledge, the updates on relay node selection and power strategies, which incurs the frequent exchange of information. The requirement of significant communication overheads among nodes not only impede fully distributed solutions, but also disagrees with the energy-saving goal. In this work, we formulate the energy-efficient relay management problem as a discrete, stochastic game for a multi-source multi-relay ad hoc network. In the proposed game, each potential relay node is viewed as a player to search for the best action in the probability space with the incomplete distributed information. We investigate the achievable performance of the proposed game in terms of the existence of Nash equilibrium, its expression by using the support and programming methods, and its Pareto optimality. Moreover, we propose a low-complexity, distributed learning algorithm based on the linear reward-inaction procedure. The properties of convergence and learning rate of the algorithm are analyzed.

In this paper we compare the influence of intra-cell connections in GSM network and the influence of the limitation of the number of traffic sources in one GSM cell on call blocking. It is proved that the influence of intra-cell connections on the loss probability is larger than the influence of limited number of traffic sources. The results are obtained by calculation and by simulation.

Joint decoding of all users' data symbols can be distributed across a network of interacting base stations by message passing techniques. Instead of discrete belief propagation, the Gaussian belief propagation algorithm (GaBP) is proposed. The approximate message passing algorithm has lower computational complexity. Numerical results show a near optimal performance of the data estimation in terms of the minimum mean square error sense or bit error rate.

This paper studies the channel exploration problem for the distributed opportunistic spectrum access (D-OSA) systems, where multiple secondary users (SUs) sequentially sense multiple licensed channels and access one of idle channels. SUs operate on a frame-by-frame basis and need to sense channels at the beginning of each frame. According to the stopping rule, SUs determine to stop at the sensed channel or continue to sense next channels. However, the optimal design in the scenario of multiple SUs with the multiple licensed channels is difficult to realize for D-OSA systems. To solve this problem, we introduce an adjusted function considering the interactions among SUs, and then propose an adaptive stopping rule to improve the performance of the multi-user system. Simulation results are provided to show the effectiveness of the adaptive stopping rule and the significant improvement of the throughput performance.

Cognitive radio (CR) technology is a solution to solve the lack of spectrum by allowing the secondary user to use licensed bands. There are several potential security challenges for cognitive radio like jamming, primary user emulation (PUE) and lion attack. The lion attack is a multi-layer attack that has effects on two layers. It uses PUE or jamming attack in physical layer to disrupt transmission control protocol (TCP) in transport layer. Since transport layer is unaware of physical layer situation, when it occurs to an unacknowledged packet, there is no way to distinguish between congestion and disconnection in the physical layer. So the window size of TCP would be decreased because of a wrong decision caused by unawareness. To mitigate the lion attack the cross layer design is usually used to freeze its window size during frequency handoff. The main issue in this solution is finding the best strategy for freezing. In this paper, we propose a dynamic method for freezing and performing frequency handoff to counter lion attack. Also a learning model based on Markov decision process (MDP) is applied. By using the proposed method, the secondary user can choose an optimal strategy in both physical and transport layers to reduce the effect of lion attack.