The unfairness problem among TCP connections has been proved to be very severe in the IEEE 802.11-based wireless ad hoc networks because the hidden station problem still exists and the binary exponential backoff algorithm always favors the latest successful station. In this paper, a novel protocol, neighbor-medium-aware MAC (NEMA-MAC), is proposed to improve the TCP fairness. By adding a medium (channel) state field in the head of the traditional IEEE 802.11 MAC frame, the NEMA-MAC protocol provides a communication mechanism to resolve the hidden station problem. In addition, when a collision occurs, the new backoff algorithm makes the senders cooperatively adjust the contention window according to their local and neighbors' channel usage indexes. The simulation results show that TCP sessions can acquire satisfying fairness and increase the throughput in the NEMA-MAC-based multihop ad hoc networks.

TCP performance in the IEEE 802.11-based multihop ad hoc networks is extremely poor, because the congestion control mechanism of TCP cannot effectively deal with the problem of packet drops caused by mobility and shared channel contention among wireless nodes. In this paper, we present a cross-layer method, which adaptively adjusts the TCP maximum window size according to the number of RTS (Request To Send) retry counts of the MAC layer at the TCP sender, to control the number of TCP packets in the network and thus decrease the channel contention. Our simulation results show that this method can remarkably improve TCP throughput and its stability.

Cognitive radio has emerged as an efficient approach to reusing the licensed spectrums. How to appropriately set parameters of secondary user (SU) plays a rather important role in constructing cognitive radio networks. In this letter, we have analyzed the theoretical value of SUs' density, which provides a standard for controlling the number of SUs around one primary receiver, in order to guarantee that primary communication links do not experience excessive interference. The simulation result of secondary density well matches with the theoretical result derived from our analysis. Additionally, the achievable rate of secondary user under density control is also analyzed and simulated.

The selection cooperation is a basic and attractive scheme of cooperative diversity in the multiple relays scenario. Most previous schemes of selection cooperation consist only one relay-stage in which one relay is selected to retransmit, and the signal from the selected relay is not utilized by other relays. In this paper, we introduce a two relay-stage selection cooperation scheme. The performance can be improved by letting all other relays to utilize the signal from the first selected relay to make another selection and retransmission in the second relay-stage. We derive the closed-form expression of the outage probability of the proposed scheme in the high SNR regime. Both theoretical and numerical results suggest that the proposed scheme can reduce the outage probability compared with the traditional scheme with only one relay-stage. Furthermore, we demonstrate that more than two relay-stage can not further reduce the outage probability. We also study the dependence of the proposed scheme on stage lengths and topology, and analyze the increased overhead.

A new theoretical approach for the evaluation of the in-band nonlinear distortion effects on the performance of DS-CDMA systems is presented. Rather than widely used models of treating the effects of nonlinear distortion as additive Gaussian noise, the new approach is based on the asymptotic clipping and shot noise theories, which offer important insights into true nature of clipping process and can be further extended to many communications systems with high PAPR and peak-limited nonlinearities.

In this article, we present a scattered pilot aided channel estimation and tracking technique for MIMO-OFDM systems. First we extend Li's estimation algorithm to scattered pilot-aided case. Then a scattered pilot-aided tracking scheme is developed to track the time-varying MIMO channel. The algorithms we present reduce the system overhead and channel estimation complexity to a low level with acceptable performance degradation. Simulations of a MIMO-OFDM system with four-transmit and four-receive antennas show that the new algorithm has better performance than Li's algorithm in time-varying MIMO channels.

Carrier frequency and symbol timing errors may greatly degrade the performance of the orthogonal frequency division mulitplexing (OFDM) system, especially in multipath environment. In this paper, we explore the cyclostationarity of OFDM signals, which only relies on second order statistics, to estimate the synchronization offset. First, a coarse carrier frequency offset estimator for multipath environment is developed using the second order statistics of the received OFDM signal. It has a wide capture range though not accurate. Second, we introduce a new synchronization algorithm based on cyclostationarity and matched filter theories, which can get the maximal estimation SNR in multipath environment. Both estimators utilize channel state information to achieve better estimation performance and are non-pilot aided. They can be combined to form a whole OFDM synchronizer for multipath environment. Finally, simulations confirm the performance of the estimation algorithm.

We present a simple decoding algorithm that modifies soft bit-flipping algorithm for decoding LDPC codes. In our method, a new parameter is explored to distinguish the variables (symbols) belonging to the same number of unsatisfied constraints. A token is also assigned in the method to avoid repeated flipping of the same variable, rather than using a constant taboo length. Our scheme shows a similar computational load as the taboo-based algorithm, while having a similar decoding performance as the belief propagation algorithm.

In sentiment classification, conventional supervised approaches heavily rely on a large amount of linguistic resources, which are costly to obtain for under-resourced languages. To overcome this scarce resource problem, there exist several methods that exploit graph-based semi-supervised learning (SSL). However, fundamental issues such as controlling label propagation, choosing the initial seeds, selecting edges have barely been studied. Our evaluation on three real datasets demonstrates that manipulating the label propagating behavior and choosing labeled seeds appropriately play a critical role in adopting graph-based SSL approaches for this task.

This paper introduces a random selection cooperation scheme that takes the Decode-and-Forward (DF) approach to solve the unfairness problem in selection cooperation. Compared to previous work which obtained fairness but introduced performance loss, the proposed scheme guarantees fairness without performance loss. Its essence is to randomly select from the relays that can ensure the successful communication between the source and the destination, rather than to select the best relay. Both a theoretical analysis and simulation results confirm that the proposed scheme could achieve fairness and introduce no performance loss. We also discuss the conditions under which the proposed scheme is practical to implement.

The enormous capacity potential of multiple-input multiple-output (MIMO) is based on some unrealistic assumptions, such as the complete channel state information (CCSI) at the receiver and Gaussian distributed data. In this paper, in frequency-flat Rayleigh fading environment, we investigate the ergodic capacity of MIMO systems with M-ary phase-shift keying (MPSK) modulation and superimposed pilots for channel estimation. With linear minimum mean square error (LMMSE) channel estimation, the optimal pilots design is presented. For the mathematical tractability, we also derive an easy-computing closed-form lower bound of the channel capacity. Furthermore, the optimal power allocation between the data and pilots is investigated by numerical optimization. It is shown that more power should be devoted to the data in low SNR environments and to the pilots in high SNR environments.

Discrete Wavelet Multi-carrier Transceiver (DWMT) system, which can be viewed as a kind of OFDM, has many advantages because it uses wavelets as its base functions. In this paper we present a new sub-carrier frequency offset correction method for DWMT systems with little assistant information. The essential ideal of this algorithm is: when an orthogonal multi-carrier system is of perfect frequency synchronize, the demodulated signals of different sub-carriers are independent of each other. Whereas when frequency offset exists, intercarrier interference will distort the demodulated signal, i.e. every demodulated signal is the sum of several modulated signals' projects on the demodulating frequency. So the adjacent demodulated signals consist of the element of the same modulated signal, and these demodulated signals are correlated with each other. The degree that they correlated with each other depends on sub-carrier relative frequency offset. Since that little assistant information is used in this algorithm the spectrum efficiency can be largely increased. Simulation results shown that if the number of the sub-carrier of the DWMT system is bigger than 1000, the relative frequency offset can be limited in 2%.

Most applications can adapt their coding techniques and sending rates according to the network congestion and the resource needed can be provided at the beginning of the transmission. So traditional Differentiated Services (DiffServ) model is too rigid to them. In this paper, we are seeking a balance between the relative DiffServ and the absolute DiffServ and propose a new Diffserv model, a relative Differentiated Service model with admission control, which suits the adaptive application. By providing the proportional differentiated services in core routers and loss-rate based CAC control in edge routers, we can make both the network and the users adaptive: the network is adaptive to the traffic load and the users is adaptive to the network congestion. This model is promising to the elastic but unpredictable traffic, such as IP telephony or other multimedia applications.

Among the cognitive radio technologies, cooperative spectrum sensing has been corroborated to be an effective approach to counter channel fading. Recent research about it is mainly with the assumption that secondary users (SUs) are synchronous with primary users (PUs). In this letter, we discuss the asynchronous situation for the first time, which means SUs have no idea about the communication time table of PUs' network. Based on the ON/OFF channel model, we derive the detection and false alarm probabilities, and the optimal sensing parameters under such asynchronous scenario. Simulation results are shown in the end.

Dynamic spectrum access has become a focal issue recently, in which identifying the available spectrum plays a rather important role. Lots of work has been done concerning secondary user (SU) synchronously accessing primary user's (PU's) network. However, on one hand, SU may have no idea about PU's communication protocols; on the other, it is possible that communications among PU are not based on synchronous scheme at all. In order to address such problems, this paper advances a strategy for SU to search available spectrums with asynchronous MAC-layer sensing. With this method, SUs need not know the communication mechanisms in PU's network when dynamically accessing. We will focus on four aspects: 1) strategy for searching available channels; 2) vacating strategy when PUs come back; 3) estimation of channel parameters; 4) impact of SUs' interference on PU's data rate. The simulations show that our search strategy not only can achieve nearly 50% less interference probability than equal allocation of total search time, but also well adapts to time-varying channels. Moreover, access by our strategies can attain 150% more access time than random access. The moment matching estimator shows good performance in estimating and tracing time-varying channels.