Wireless sensor network (WSN) has attracted a lot of interest for its wide range of practical applications. The energy-resource limitation of WSN demands transmissions between sensor nodes to be high efficiency. Random linear network coding (RLNC) exploits the broadcast and distributed nature of WSN to improve the throughput of network. The throughput gain brought by RLNC grows up as the generation size increased, while the decoding complexity has a cubic growth, being unacceptable for the energy-resource limited WSN. In this paper, we propose a segment linear network coding (SLNC) scheme which reduces the decoding complexity dramatically through adding constraints to the encoding coefficients and dividing a complex matrix inverse operation into several simple ones at receiver. Proved by theoretical analysis and simulation results, we show that SLNC achieves a fairly low decoding complexity with seldom increase on the overhead of network.

In this paper, we study the expected density of progress for wireless ad hoc networks with Nakagami-m fading. The expected density of progress is defined as expectation of the product between the number of simultaneous successful transmission per unit area and the distance towards the destination. By considering three next hop receiver (RX) selection strategies, i.e., nearest RX selection strategy, random RX selection strategy and furthest RX selection strategy, we derive the closed-form expressions to the expected density of progress. Numerical results show that, when the terminal density is small, the expected density of progress with nearest RX selection strategy is nearly the same as that with furthest RX selection strategy, and the expected density of progress with random RX selection strategy is the lowest; when the terminal density is larger, the nearest RX selection strategy has the largest expected density of progress, and furthest RX selection strategy has the smallest expected density of progress.

As the date rates and bandwidths of communication systems scale up, low-precision (e.g., 1-4 bits) analog-to-digital converter (ADC) is one approach to reduce the cost and power consumption for sampling rates on the order of gigahertz. Because of the significant quantization error of the low-precision ADCs, the conventional digital automatic gain control (AGC) is not applicable any more. In this work, we investigate the problem of AGC for pulse amplitude modulation (PAM) signaling over the AWGN channel. First, the optimal thresholds are derivated by maximizing the Fisher information. Then a particle filter based estimator is proposed. We divide the training sequence into several slots. In each slot, particles are generated to approximate the distribution of the input signal amplitude, which is updated basing on the quantizer outputs in previous slots. We adjust the thresholds according to the amplitude particles of the input training signal and finally obtain a maximum a posteriori probability (MAP) estimate. We obtain notable performance in terms of uncode bit error rate (BER), compared with one-shot maximum likelihood (ML) estimator with the same training length. The performance is closed to that of ideal AGC over different input amplitude values.

In this paper, we introduce optimized distributed bell laboratory layered space-time (OD-BLAST) for cooperative communication in wireless relay networks. Every potential relay node is equipped with a signal antenna, and the set of cooperating nodes is a priori unknown. In order to avoid the centralized stream and pilot allocation between cooperating nodes, a fixed signature vector (SV) is assigned for each potential relay node in the network. We analyze the constraints on the proposed schemes, and derive an optimization criterion for the SVs. A numerical method for SV design is provided and compared with randomly generated SVs. Simulation results confirm that the performance loss of OD-BLAST compared to centralized distributed BLAST is small for large number of cooperative relay nodes.

We consider a two-user Gaussian interference channel with a relay. Specifically, two source-destination pairs and the relay share a single common channel, and the relay receives messages from both sources, and assists them in communicating the messages to their respective destinations. We propose two relaying schemes using "amplify-and-forward" (AF). For each of two modes considered, we characterize the achievable sum rate and present upper bounds as functions of relay locations.

We propose a optimal power allocation algorithm for Distributed Sensing networks under the assumption of a group of sensors observe the same quantity in independent additive observation noises with possibly different variances. Each node computes a local statistic and communicates it to the fusion center over rayleigh fading wireless channels. At the fusion, the linear minimum mean square error (LMMSE) is used. Sensor networks in which energy is a limited resource, our goal is to minimize the distortion under certain power constraints. In this paper, for a given power constraints, equal power transmission strategy and the optimal power allocation strategy is considered. In the later, we first discuss the problem with only a sum power constraint, and then discuss the general case with both sum and individual power constraints. Finally, we demonstrate the applicability of our results through numerical examples. Result shows that the optimal distributed estimation algorithm for homogeneous sensor networks achieves the power gain by turning off sensors that with bad channels and bad observation quality.

In this paper, a decode-and-forward (DF) cooperative diversity scheme is considered for dynamic relay networks, where each node is equipped with a single antenna. A randomized space-time block coding (STBC) cooperative relaying scheme has been proposed to get spatial diversity gains without centralized control information. However, it can not get maximum diversity gain when the number of active relay nodes is small. In this paper, we propose a limited feedback scheme to improve the bit error rate (BER) performance of the randomized STBC scheme. Simulation results reveal that the proposed feedback scheme can achieve almost the same BER performance as the centralized STBC scheme in some channel conditions. In addition, it does not degrade the performance of the randomized STBC scheme even with a large feedback delay.

We consider secondary user performing opportunistic spectrum access (OSA) over multiple correlated channels occupied by primary users. The channel occupancy states can be modeled as a discrete-time Markov process. Due to hardware and energy limitations, secondary user can choose only one channel to sense in each slot. Based on the sensing outcome, it decides its access action. Hence, channel selection scheme (i.e. sensing policy) at the MAC layer is of vital importance for secondary user's throughput and sensing policy design can be formulated as a partially observable Markov decision process (POMDP). Unlike other research, in which case the channel occupancy states (induced by primary users) evolving independently among multiple channels, our work emphasizes on the case that multiple channels are not independent any more, then they evolve dependently. By adopting myopic sensing, which is an approach with low complexity to implement POMDP, we propose a myopic sensing policy exploiting the channel correlation in this paper. Numerical results illustrate that the proposed sensing policy improves the throughput of the secondary user either with or without the presence of spectrum sensing error.

We consider the issue of opportunistic spectrum access (OSA) in cognitive radio network. By modeling the channel occupancy states induced by the primary users as a discrete-time Markov process, the channel selection scheme of the secondary users at the MAC layer can be formulated as a partially observable Markov decision process (POMDP). Under the POMDP framework, myopic sensing (which is a kind of channel selection scheme) is adopted with the assumption that occupancy of each channel evolves independently. In this paper, differing from former research assuming independent channel occupancy, we investigate into the case when correlation exists across different channels. By exploiting the channel correlation information, we propose two multi-channel myopic sensing policies: one with full-dimension belief vector, and the other with reduced-dimension belief vector. The sensing policies are given out under different PHY layer conditions: with or without the presence of spectrum sensing error. Simulation results illustrate that the proposed sensing policies can improve the throughput of the secondary users as time increases.

Relay stations (RSs) are usually used to enhance the signal strength of the mobile stations (MSs) close to the cell boundary. However, the introduction of RSs to the cellular networks increases the interference to the MS served by the base station (BS) under spatial multiplexing mode. In this paper, we propose a method which can cancel the interference through a novel use of dirty paper coding (DPC). Then, under a practical spatial multiplexing frame structure, we evaluate the cellularrelay system performance under three scheduling algorithms, Round Robin (RR) algorithm, Maximum Signal to Interference and Noise Ratio (MaxSINR) algorithm and Proportional Fair (PF) algorithm. Simulation and analytical results show that the spectral efficiency (SE) of cellular-relay system can be dramatically increased by 30% by the proposed interference cancellation method, and RR algorithm achieves the highest gain, while the gain of MaxSINR algorithm is limited gain in our scheme.

This paper discusses on the fair resource allocation in OFDMA two-hop cooperative relaying cellular networks which consist of a single base station (BS), dedicated fixed relay stations (RSs) and user stations (USs). By assuming the relay strategy employed on each subcarrier is adaptively selected among direct transmission, amplify-and-forward (AF) and decode-and-forward (DF) according to different channel conditions, we formulate a fair subcarrier assignment, relay station and relay strategy selection problem with QoS constraints in terms of user's minimum rate requirement. The formulated problem is a binary integer programming (BIP) problem which is NP-complete, so a simple suboptimal algorithm is proposed to manage the network resources. Simulations demonstrate the proposed algorithm obtains near optimal solution with low complexity and achieves a good tradeoff between the overall system performance and the fairness among users.

In this paper, a cooperative spatial multiplexing scheme is considered for dynamic relay networks. We assume that each relay node is equipped with a single antenna. To obtain spatial multiplexing gains, the distributed multiple-input multiple-output (MIMO) scheme, in which cooperating nodes act as elements of a multi antenna system, has been proposed in many papers. Since the nodes need to know their specific stream and pilot index, either internode communication or a central control unit is required. Our design objective is to obtain spatial multiplexing gains while eliminating the need for stream and pilot allocation. We introduce a novel randomized strategy that decentralize the transmission of multi streams from a set of distributed relay nodes. We analyze the constraints on the random scheme, and propose a limited feedback scheme to further improve its performance.

In this paper, we consider decentralized estimation of a noise-corrupted deterministic parameter in wireless sensor networks with the aid of relay. We propose a new relay-aided decentralized estimation scheme by which relay collects the overheard messages from sensors, computes a local message, and then sends it to a destination. Besides, we develop the sensor selection policies to select the most appropriate sensor for observation transmission, and then propose the opportunistic scheduling protocol for decentralized estimation to allow relay to perform cooperation transmission opportunistically. Numerical simulation shows the proposed strategies can provide better estimation performance without any bandwidth loss.

Chord is one of the best known lookup protocols for structured peer-to-peer (P2P) networks. Nodes in Chord can be viewed as being placed on a one-dimensional ring. In this paper, we present a novel concept of bi-dimensional P2P, in which all nodes are placed onto a square rather than a ring to enable the flexible configuration of ring(s). Diverse ring configuration schemes form a uniform protocol family called multi-ring bi-dimensional (MRBD) protocols, and Chord can be considered as MRBD-1. Different configurations of rings provide various performance to satisfy diverse user requirements. We study examples of MRBD from both theoretical analysis and simulations. The results validate the effectiveness of MRBD in improving P2P lookup performance.

In this paper, we focus on the Markov model of IEEE 802.11 distributed coordination function with power saving mode. The throughput evaluation is based on the model, with the comparison with the simulation result for validation. Furthermore, we notice that after each beacon transmission, there're more stations in contention than usual. Excessive contention results in high collision probability and low throughput. To solve this problem, we propose a downlink access scheme which can be used in both the basic access scheme and the access scheme with RTS/CTS. This novel scheme enables AP to constrain the number of stations in contention to be an optimal value. Simulation results prove the performance improvement declared. The proposed scheme can be extended for multi-rate or multi-service WLANs.

In this paper, adaptive transmission using channel rank for MIMO-OFDM system is considered. Different transmission schemes have different diversity and multiplexing tradeoff characters. Adjusting MIMO transmission scheme according to channel quality indicator (CQI) or channel state information will improve system performance. We propose a new transmission adaptation solution depending on two-dimensional channel quality indicators with the aim to enhance system throughput performance. This is realized by using different space-time modulation schemes, which support different data streams. The proposed scheme is verified by simulation with practical radio propagation models, where different correlation scenarios are considered. In contrast to fixed transmission mode and only SNR based adaptive method, the proposed two dimensional CQI solution has more throughput gain with limited feedback.

Current research on wireless TCP always assumes that link layer utilizes the hybrid ARQ scheme without packet combining for error recovery. However, there are two other hybrid ARQ schemes with packet combining used to recover error at link layer. Little attention is paid to how the two schemes affect the wireless TCP. In this paper, we study the effect of the three hybrid ARQ schemes on the spurious TCP timeouts over wireless link via extensive simulation and numerical analysis. We find that the hybrid ARQ schemes with packet combining can avoid spurious TCP time more efficiently than the ARQ scheme without packet combining when the persistency of ARQ schemes is full. This suggests that the hybrid ARQ schemes with packet combining and fully persistency policy is enough to improve TCP performance over wireless link.

In this paper, we propose a multistage soft decision equalization (SDE) technique using max-log-MAP sphere decoder (MLMSD) for block transmission over frequency selective multi-input multi-output (MIMO) channels. Using the Toeplitz structure of the channel matrix, we convert the general signal model into a series of small-sized sub-signal models. We propose to use MLMSDs based on these sub-models to iteratively cancel interferences and get the estimations of the transmitted symbols. Simulation shows that when the block size is large, the proposed algorithm outperforms the Schnorr-Euchner sphere decoder and the probability data association SDE with a reasonable computational complexity in full-rank MIMO channels.

In this paper, we propose a multistage soft decision equalization (SDE) technique using max-log-MAP sphere decoder (MLMSD) for block transmission over frequency selective multi-input multi-output (MIMO) channels. Using the Toeplitz structure of the channel matrix, we convert the general signal model into a series of small-sized sub-signal models. We propose to use MLMSDs based on these sub-models to iteratively cancel interferences and get the estimations of the transmitted symbols. Simulation shows that when the block size is large, the proposed algorithm outperforms the Schnorr-Luchner sphere decoder and the probability data association SDL with a reasonable computational complexity in full-rank MIMO channels

Subcarrier allocation schemes for SISO-OFDM systems in multiuser downlink scenario is well-documented. In this paper, with the goal of maximizing channel capacity, we extend it to MIMO-OFDM systems and propose a novel resource scheduling scheme with dynamic antenna and subcarrier allocation. This is done by maximizing the number of equivalent parallel subchannels in space-frequency structure and corresponding channel fading coefficients in frequency domain. The results show that our proposed algorithm outperforms multiuser MIMO-OFDM systems with static time-division multiple access (TDMA) technique which employ fixed and predetermined time-slot allocation scheme

A novel parallel receiver is proposed for turbo-coded multi-antenna system, which combines detection and decoding, and fully utilizes the original information in terms of Shannon information theory. We modify the conventional maximum a posteriori (MAP) BCJR algorithm to decode multi-antenna interference signal directly. This algorithm is insensitive to multi-antenna structure, not like space-time coding (STC), layered space-time (LST), and also obtains receive diversity by combining extrinsic information or log-likelihood ratio (LLR) information. Simulation results verify the proposed receiver algorithm

Conventional automatic repeat request (ARQ) schemes perform poorly in wireless fading channels. In this paper, variable packet size adaptive modulation (AM) ARQ scheme is proposed. The performance of discrete packet size AM selective repeat (SR) ARQ schemes for Rayleigh fading channels is analyzed and simple analytical expressions of its throughput are presented. The optimum switching thresholds that maximize the throughput are found. Theoretic analysis and numerical results indicate that a small number of packet sizes per modulation mode can get good performance in fading channels.

Unlike wired networks, random packet loss due to bit errors may cause significant performance degradation of the transmission control protocol (TCP). We propose and study a novel end-to-end congestion control mechanism called TCP/spl I.bar/LD (lose detection) that is simple and effective for dealing with random packet loss . The simulation results show that our scheme can achieve significant throughput improvements without adversely affecting other concurrent TCP connections, including other concurrent Reno connections.

This contribution proposes a novel synchronization approach for cyclic prefix (CP) based systems such as OFDM and CP-based single carrier systems. Short-time FFT is applied to the received signal, which results the its 2-D spectrum. By detecting the flat region on the 2-D spectrum in time direction, the instants where inter-symbol interference (ISI) is absent are determined for symbol timing and carrier synchronization. Simulations results on its performance in AWGN and multipath fading environment as well as its robustness against duration of channel impulse response (CIR) and frequency offset are presented.

Space-time codes are the joint design of channel coding, modulation, transmit and receive diversity to provide the best tradeoff between data rate, diversity advantage, and code complexity. Specific codes improve the transmission performance in wireless fading channel by providing both the diversity advantage and the coding advantage, where channel state information (CSI) is available at the receiver. But in practice, it is very difficult to estimate the CSI accurately because of the characteristic of wireless fading channel: multi-path fading and time-variance. Hence, a theoretical study of the symbol error rate (SEK) for orthogonal space-time block codes (OSTBC) is presented in this paper, in the absence of perfect CSI. It is proved that the squaring method used to simplify the decoding of OSTBC in [Li Xiangming et al., 2001] could also be used when there is no perfect CSI at receiver. Using this squaring method, a closed-form expression of both SNR and SER for OSTBC can also be derived under these conditions. Simulation results show that performance in the presence of the channel estimation errors is less than that with ideal condition, and that more estimation errors, means more performance loss. It is also proved through the simulations that the BER bound increases slowly when the variance of channel estimation errors is less than some little value, e.g. 0.2. So in practice, it is important to keep the variance of estimation errors less than this value.

In this paper, we apply pilot-symbol-aided estimation technique in time domain to estimate the fractional part of the normalized frequency offset in OFDM system. Moreover, we correct the frequency offset according to a general theoretical model for OFDM with frequency offset. The simulation results prove the estimation of frequency offset is precise, and the correction of frequency offset is very effective.

ARQ can guarantee an almost error free reception. But in traditional ARQ schemes, all packets are transmitted with the same modulation mode, which makes its performance poor in fading channels. Adaptive modulation (AM) is an efficient way to improve spectral efficient of the system. Combining ARQ and AM will give a more promising performance. In this paper, the throughput of SR-ARQ schemes with adaptive modulation systems is analyzed. Simple analytical expressions are presented. Numerical results from the analysis and some discussion are given.

We present a squaring method to simplify the decoding of orthogonal space-time block codes in a wireless communication system with an arbitrary number of transmit and receive antennas. Using this squaring method, a closed-form expression of signal-to-noise ratio after space-time decoding is also derived. It gives the same decoding performance as the maximum-likelihood ratio decoding while it shows much lower complexity.

Echo cancellation in two-wire full-duplex data transmission is usually performed with data-driven transversal filters. In this paper, we propose a new scheme for a microprocessor-based digital adaptive echo canceler. We call it "memory-tap echo canceler" (MTEC) because its taps are made of time-delayed L groups of memory registers. Since the estimated echo signals are directly derived from the binary-nature data, the manipulations involved are multiplication-free for any modulation scheme (baseband, or passband). A theoretical analysis of adaptation, convergence, and computational complexity is given, and the convergence characteristic of MTEC is verified by the computer simulations. Finally, we present some preliminary experimental results for an Intel 8086 microprocessor-based 2400 bit/s echo canceler.