In heterogenous networks (HetNets), the deployment of small cells with the reuse of limited frequency resources to improve the spectral efficiency results in cross- and co-tier interference. In addition, the excessive power usage in such networks is also a critical problem. In this paper, we propose precoding and postcoding schemes to tackle interference and energy efficiency (EE) challenges in the two-tier downlink multiple-input-multiple-output (MIMO) HetNets. We propose transmission strategies based on hierarchical partial coordination (HPC) of the macro cell and small cells to reduce channel state information (CSI) exchange and guarantee the quality of service (QoS) in the upper tier with any change of network deployment in the lower tier. We employ the interference alignment (IA) scheme to cancel cross- and co-tier interference. Additionally, to maximize the EE, power allocation schemes in each tier are proposed based on a combination of Dinkelbach's method and the bisection searching approach. To investigate insights on the optimization problem, a theoretical analysis on the relationship between the maximum achievable EE and the transmit power is derived. Simulation results prove the superior EE performance of the proposed EE maximization scheme over the sum rate maximization approach and confirm the validity of our theoretical findings.

A dual-hop amplify-and-forward (AF) relaying system with beamforming is analyzed over η-µ fading channels that includes Nakagami-m, Nakagami-q (Hoyt), and Rayleigh fading channels as special cases. New and exact expressions for the outage probability (OP) and average capacity are derived. Moreover, a new asymptotic analysis is also conducted for the OP and average capacity in terms of basic elementary functions which make it easy to understand the system behavior and the impact of channel parameters. The viability of the analysis is verified by Monte Carlo simulations.

Iterative channel estimation and decoding receivers have evolved over the years, most especially with Turbo and LPDC codes. Nevertheless, few works have determined the performance of symbol level Reed-Solomon (RS) codes in iterative receiver structures. The iterative channel estimation and symbol level RS decoding receiver structure found in literature concentrate on M-QAM systems over flat Rayleigh fading channels. In this paper, attention is focused on the performance of RS codes in iterative channel estimation and decoding receiver structures for Orthogonal Frequency Division Multiplexing (OFDM) systems on frequency-selective Rayleigh fading channels. Firstly, the paper extends the Koetter and Vardy (KV) RS iterative receiver structure over flat Rayleigh fading channels to frequency-selective Rayleigh fading channels. In addition, the paper develops a symbol level RS iterative receiver structure for OFDM systems on frequency-selective Rayleigh fading channels based on the Parity-check matrix Transformation Algorithm (PTA). The performance of the RS-KV and RS-PTA iterative receiver structures for OFDM systems are documented through computer simulation. The simulation results verify that both iterative receiver structures are suitable for real time RS OFDM wireless applications. The results also show that the developed RS-PTA iterative receiver structure is a low complexity and high performance alternative to the RS-KV iterative receiver structure.

In the present paper, we propose a broadcast ARQ protocol based on the concept of index coding. In the proposed scenario, a server wishes to transmit a finite sequence of packets to multiple receivers via a broadcast channel with packet erasures until all of the receivers successfully receive all of the packets. In the retransmission phase, the server produces a coded packet as a retransmitted packet based on the side-information sent from the receivers via feedback channels. A notable feature of the proposed protocol is that the decoding process at the receiver side has low decoding complexity because only a small number of addition operations are needed in order to recover an intended packet. This feature may be preferable for reducing the power consumption of receivers. The throughput performance of the proposed protocol is close to that of the ideal FEC throughput performance when the erasure probability is less than 0.1. This implies that the proposed protocol provides almost optimal throughput performance in such a regime.

In this paper, we study the degrees of freedom (DoF) of a multiple-input multiple-output (MIMO) multiway relay channel (mRC) with two relays, two clusters and K (K≥3) users per cluster. We consider a clustered full data exchange model, i.e., each user in a cluster sends a multicast (common) message to all other users in the same cluster and desires to acquire all messages from them. The DoF results of the mRC with the single relay have been reported. However, the DoF achievability of the mRC with multiple relays is still an open problem. Furthermore, we consider a more practical scenario where no channel state information at the transmitter (CSIT) is available to each user. We first give a DoF cut-set upper bound of the considered mRC. Then, we propose a distributed interference neutralization and retransmission scheme (DINR) to approach the DoF cut-set upper bound. In the absence of user cooperation, this method focuses on the beamforming matrix design at each relay. By investigating channel state information (CSI) acquisition, we show that the DINR scheme can be performed by distributed processing. Theoretical analyses and numerical simulations show that the DoF cut-set upper bound can be attained by the DINR scheme. It is shown that the DINR scheme can provide significant DoF gain over the conventional time division multiple access (TDMA) scheme. In addition, we show that the DINR scheme is superior to the existing single relay schemes for the considered mRC.

In this paper, we propose two secure multiuser multiple-input multiple-output (MIMO) transmission approaches based on interference alignment (IA) in the presence of an eavesdropper. To deal with the information leakage to the eavesdropper as well as the interference signals from undesired transmitters (Txs) at desired receivers (Rxs), our approaches aim to design the transmit precoding and receive subspace matrices to minimize both the total inter-main-link interference and the wiretapped signals (WSs). The first proposed IA scheme focuses on aligning the WSs into proper subspaces while the second one imposes a new structure on the precoding matrices to force the WSs to zero. In each proposed IA scheme, the precoding matrices and the receive subspaces at the legitimate users are alternatively selected to minimize the cost function of a convex optimization problem for every iteration. We provide the feasible conditions and the proofs of convergence for both IA approaches. The simulation results indicate that our two IA approaches outperform the conventional IA algorithm in terms of the average secrecy sum rate.

In this paper, we investigate the problem of maximizing the weighted sum outage rate in multiuser multiple-input single-output (MISO) interference channels, where the transmitters have no knowledge of the exact values of channel coefficients, only the statistical information. Unfortunately, this problem is nonconvex and very difficult to deal with. We propose a new, provably convergent iterative algorithm where in each iteration, the original problem is approximated as second-order cone programming (SOCP) by introducing slack variables and using convex approximation. Simulation results show that the proposed SOCP algorithm converges in a few steps, and yields a better performance gain with a lower computational complexity than existing algorithms.

Although many approaches about ideal channels have been proposed in previous researches, few authors considered the situation of nonideal communication links. In this paper, we study the problem of distributed decision fusion over nonideal channels by using the scan statistics. In order to obtain the fusion rule under nonideal channels, we set up the nonideal channels model with the modulation error, noise and signal attenuation. Under this model, we update the fusion rule by using the scan statstics. We firstly consider the fusion rule when sensors are distributed in grid, then derive the expressions of the detection probability and false alarm probability when sensors follow an uniform distribution. Extensive simulations are conducted in order to investigate the performance of our fusion rule and the influence of signal-noise ratio (SNR) on the detection and false alarm probability. These simulations show that the theoretical values of the global detection probability and the global false alarm probability are close to the experimental results, and the fusion rule also has high performance at the high SNR region. But there are some further researches need to do for solving the large computational complexity.

In this paper, the average symbol error probability (SEP) performance of decode-and-forward (DF) relaying mobile-to-mobile (M2M) systems with transmit antenna selection (TAS) over N-Nakagami fading channels is investigated. The moment generating function (MGF) method is used to derive exact SEP expressions, and the analysis is verified via simulation. The optimal power allocation problem is investigated. Performance results are presented which show that the fading coefficient, number of cascaded components, relative geometrical gain, number of antennas, and power allocation parameter have a significant effect on the SEP.

A brain-computer interface (BCI) translates the brain activity into commands to control external devices. P300 speller based character recognition is an important kind of application system in BCI. In this paper, we propose a framework to integrate channel correlation analysis into P300 detection. This work is distinguished by two key contributions. First, a coefficient matrix is introduced and constructed for multiple channels with the elements indicating channel correlations. Agglomerative clustering is applied to group correlated channels. Second, the statistics of central tendency are used to fuse the information of correlated channels and generate virtual channels. The generated virtual channels can extend the EEG signals and lift up the signal-to-noise ratio. The correlated features from virtual channels are combined with original signals for classification and the outputs of discriminative classifier are used to determine the characters for spelling. Experimental results prove the effectiveness and efficiency of the channel correlation analysis based framework. Compared with the state-of-the-art, the recognition rate was increased by both 6% with 5 and 10 epochs by the proposed framework.

In this paper, we derive two simple asymptotic closed-form formulas for the average bit error probability (BEP) of differential quaternary phase shift keying (DQPSK) with Gray encoding and a simple asymptotic approximation for the average symbol error probability (SEP) of doubly-differential quaternary phase shift keying (DDQPSK) in Nakagami-m fading channels. Compared with the existing BEP/SEP expressions, the derived concise formulas are much more effective in evaluating the asymptotic properties of DQPSK/DDQPSK with various Nakagami fading parameters, the accuracy of which is verified by extensive numerical results.

In 1973, Arimoto proved the strong converse theorem for the discrete memoryless channels stating that when transmission rate R is above channel capacity C, the error probability of decoding goes to one as the block length n of code word tends to infinity. He proved the theorem by deriving the exponent function of error probability of correct decoding that is positive if and only if R>C. Subsequently, in 1979, Dueck and Körner determined the optimal exponent of correct decoding. Arimoto's bound has been said to be equal to the bound of Dueck and Körner. However its rigorous proof has not been presented so far. In this paper we give a rigorous proof of the equivalence of Arimoto's bound to that of Dueck and Körner.

Network coding on the physical-layer has recently been widely discussed as a potentially promising solution to the wireless access problem in a relay network. However, the existing research on physical-layer network coding (PNC), usually assumes that the symbol timing of the nodes is fully synchronized and hardly investigates the unavoidable symbol timing errors. Similar to many telecommunication systems, symbol timing plays a critical role in PNC and precise alignment has to be provided for the encoding. In this work, we propose a novel symbol timing algorithm with a low oversampling factor (samples per symbol) based on the a priori knowledge of the transmitted pulse shape. The proposed algorithm has the dual advantages of the low oversampling rate and high precision. The mean square error (MSE) performance is verified by simulations to be at least one order of magnitude better than that of the conventional optimum phase (OP) algorithm for a signal noise ratio (SNR) greater than 5dB.

The Satellite/Terrestrial Integrated mobile Communication System (STICS), which allows terrestrial mobile phones to communicate directly through a satellite, has been studied [1]. Satellites are unaffected by the seismic activity that causes terrestrial damage, and therefore, the STICS can be expected to be a measure that ensures emergency call connection. This paper first describes the basic characteristics of call blocking rates of terrestrial mobile phone systems in areas where non-functional base stations are geographically clustered, as investigated through computer simulations that showed an increased call blocking rate as the number of non-functional base stations increased. Further simulations showed that restricting the use of the satellite system for emergency calls only ensures the STICS's capacity to transmit emergency communications; however, these simulations also revealed a weakness in the low channel utilization rate of the satellite system [2]. Therefore, in this paper, we propose increasing the channel utilization rate with a priority channel framework that divides the satellite channels between priority channels for emergency calls and non-priority channels that can be available for emergency or general use. Simulations of this priority channel framework showed that it increased the satellite system's channel utilization rate, while continuing to ensure emergency call connection [3]. These simulations showed that the STICS with a priority channel framework can provide efficient channel utilization and still be expected to provide a valuable secondary measure to ensure emergency communications in areas with clustered non-functional base stations during large-scale disasters.

In this paper, we propose an analytical approach for adaptive decode-and-forward (ADF) relaying schemes consisting of burst data transmission based on pilot symbol assisted-channel estimation (PSA-CE) methods over quasi-static Rayleigh fading channels. At first, we focus on the error-event at relay nodes in which the transmission mode switching is carried out burst by burst, whereas previous studies assumed the transmission mode switching symbol-by-symbol, thus showing lower error rate bound. Under consideration of burst transmission for ADF relay systems, we derive exact error rate expressions which better estimate the performance of actual systems. Then, the average bit and burst error rates are derived in approximated expressions for an arbitrary link signal-to-noise ratio (SNR) related with channel estimation errors. Their accuracy is confirmed by comparison with simulation results. Furthermore, ADF relay systems with PSA-CE schemes are confirmed to select correctly decoded relay nodes without additional signaling between relay nodes and the destination node and it is verified to achieve the performance at a cost of negligible SNR loss.

The correct detection of the start of burst is very important in wideband networking radio operation as it directly affects the Time Division Multiple Access (TDMA) adaptive time slot algorithm. In this paper, we propose a robust Data Aided (DA) algorithm for burst detection in a hybrid CDMA/Adaptive TDMA based wideband networking waveform of a software defined radio. The proposed algorithm is based on a novel differentially modulated training sequence designed by using precoding sequence. The training sequence structure and precoding sequence are exploited in the calculation of proposed timing metric which is normalized by the signal energy. The precoding sequence is adequately designed for the timing metric to have a sharp peak. The algorithm shows excellent performance for multiuser scenario. It is shown through computer simulations that by increasing the active users from 1 to 8, the performance degradation is only about 1∼2dB. The proposed algorithm is compared with other algorithms and found to outperform them even in the presence of multipath fading effects. The proposed algorithm has been implemented on Field Programmable Gate Array (FPGA) platform for high data rate applications and it is shown that the results from hardware are identical to the simulation results.

In this paper, we propose a novel Carrier Frequency Offset (CFO) estimation and compensation algorithm applicable to Software Defined Radio (SDR). A two stage estimation algorithm has been proposed as a concatenation of two algorithms namely Modified Maximum Likelihood Data Aided (MMLDA) coarse frequency estimation and sample by sample residual CFO estimation. The second stage tracks the residual offset on sample by sample basis for the whole burst without using preamble. Simulation results are given for Stanford University Interim (SUI) channels to demonstrate the effectiveness of the proposed algorithm in multipath fading channel. The proposed algorithm shows better performance than the conventional two stage algorithms, even for large frequency offsets. The proposed algorithm has been implemented in software on TMS320C64x+ Digital Signal Processor (DSP) core and verified by comparing with simulation results.

In this paper, we focus on a centralized spectrum access strategy in a cognitive radio network, in which a single licensed spectrum with one primary user (PU) and several secondary users (SUs) (multiple input streams) are considered. We assume the spectrum can be divided into multiple channels and the packets from variable SUs can arrive at the system simultaneously. Taking into account the priority of the PU, we suppose that one PU packet can occupy the whole licensed spectrum, while one SU packet will occupy only one of the channels split from the licensed spectrum when that channel is not used. Moreover, in order to reduce the blocking ratio of the SUs, a buffer with finite capacity for the SUs is set. Regarding the packet arrivals from different SUs as multiple input streams, we build a two-dimensional Markov chain model based on the phase of the licensed spectrum and the number of SU packets in the buffer. Then we give the transition probability matrix for the Markov chain. Additionally, we analyze the system model in steady state and derive some important performance measures for the SUs, such as the average queue length in the buffer, the throughput and the blocking ratio. With the trade-off between different performance measures, we construct a net benefit function. At last, we provide numerical results to show the change trends of the performance measures with respect to the capacity of the SU buffer under different network conditions, and optimize the capacity of the SU buffer accordingly.

Weissman introduced a coding problem for channels with action-dependent states. In this coding problem, there are two encoders and a decoder. An encoder outputs an action that affects the state of the channel. Then, the other encoder outputs a codeword of the message into the channel by using the channel state. The decoder receives a noisy observation of the codeword, and reconstructs the message. In this paper, we show an exponential error bound for channels with action-dependent states based on the random coding argument.

This paper proposes an opportunistic feedback and user selection method for a multiuser two-way relay channel (MU-TWRC) in a time-varying environments where a base station (BS) and a selected mobile station (MS), one of K moving MSs, exchange messages during two time slots via an amplify-and-forward relay station. Specifically, under the assumption of perfect channel reciprocity, we analyze the outage probabilities of several channel feedback scenarios, including the proposed scheme. Based on the analysis, the transmission rates are optimized and the optimal user selection method is proposed to maximize the expected sum throughput. The simulation results indicate that, with opportunistic feedback, the performance can be significantly improved compared to that without feedback. Moreover, the performance is nearly identical to that with full feedback, and close to the case of perfect channel state information at BS for low mobility MSs.