A low-complexity design of multi-antenna relay processing is proposed for two-way relay networks with asymmetric data flows. The proposed scheme adopts three-phase (3P) analog network coding (ANC) which allows orthogonal transmission of two communicating nodes to overcome some disadvantages of two-phase (2P) ANC protocols. For the 3P ANC, we propose antenna selection at the relay to exploit the diversity without channel estimation and rate-aware relay power allocation (RPA) to improve the outage performance under the asymmetric rate requirements. The results show that the proposed scheme without or with RPA outperforms the conventional two-phase ANC significantly in various relay locations. It is also shown that the suboptimal RPA proposed for practical implementation provides a performance close to that of the optimal RPA.

A class of low-complexity multi-antenna relaying schemes is proposed for orthogonal frequency division multiplexing based one-way and two-way relay networks. In the proposed schemes, two single-antenna terminal nodes complete the data transfer in two time phases via a multi-antenna amplify-and-forward relay without channel state information, discrete Fourier transform (DFT), and inverse DFT. The relay signal processing consists of receive combining, power scaling, and transmit diversity, where instantaneous time domain power scaling is proposed for power scaling and power-based selection combining and cyclic delay combining are proposed for receive combining, to leverage the performance only with time domain operations. An approximation to the outage probability is also derived to predict the coded performance behavior under practical channel models. It is shown by evaluating the outage probability and coded bit error rate that the proposed schemes outperform the conventional schemes of comparable complexity.

Variable bit-rate coding introduced for effective utilization of limited communication bandwidth requires accurate classification of input signals. This paper investigates implementation of a support vector machine (SVM)-based speech/music classifier in the selectable mode vocoder (SMV) framework, which is a standard codec adopted by the Third-Generation Partnership Project 2 (3GPP2). A support vector machine is well known for its superior pattern recognition capability; however, it is accompanied by a high computational cost. In order to achieve a more practical system, three techniques are proposed for the SVM-based speech/music classifier. The first is to prune support vectors that least contribute to the output of the SVM, while the other two are aimed at reducing the number of classification requests to the SVM-based classifier by eliminating or redirecting some of the classification requests to the classifier.

We consider a relay precoding problem in a non-regenerative multiple-input multiple-output (MIMO) relay system, where the relay has the perfect channel state information of the source-relay link and only the covariance information of the relay-destination link. The average capacity seen by the relay is maximized under a relay transmit power constraint. The relay precoding problem is transformed to its equivalent power allocation problem at the relay. The optimal power allocation solution is then derived by formulating the optimization problem via difference of convex (DC) functions programming. To reduce the computational complexity, we also propose a suboptimal scheme by modifying the naive Jensen method. Furthermore, we propose the maximum eigenmode relaying (MER) scheme, which allocates the relay transmit power only to the maximum eigenmode. A necessary and sufficient condition for the MER to be asymptotically optimal is derived in the high signal-to-noise ratio (SNR) regime of the source-relay link. The performance of the proposed schemes is investigated through extensive numerical simulations.

In this paper, we propose a near maximum likelihood (ML) scheme for the decoding of multiple input multiple output systems. Based on the metric-first search method and by employing Schnorr-Euchner enumeration and branch length thresholds, the proposed scheme provides a higher efficiency than other conventional near ML decoding schemes. From simulation results, it is confirmed that the proposed scheme has lower computational complexity than other near ML decoders while maintaining the bit error rate very close to the ML performance. The proposed scheme in addition possesses the capability of allowing flexible tradeoffs between the computational complexity and BER performance.

Energy-efficient transmission technique is a very essential performance decision factor for maximizing the lifetime of energy-constrained wireless devices such as Wireless Personal Area Network (WPAN) devices. Moreover, if the WPAN is operated in conjunction with a TDMA based scheme, the assurance of QoS requirements in the actual physical transmission at each allocated time slot is another important factor to be satisfied. We therefore propose an energy-efficient and QoS aware transmission scheme for WPANs operating in conjunction with a TDMA-based contention-free medium access protocol. The proposed algorithm determines the optimum combination of transmit power, physical data rate (i.e. modulation level) and fragment size required to simultaneously minimize the energy consumption and satisfy the required QoS in each assigned time duration. The proposed algorithm demonstrated the improved performance results in terms of throughput and energy consumption via computer simulations.

In this paper, we propose a QoS guaranteed and energy-efficient transmission scheme for Wireless Personal Area Networks (WPANs), which operate in conjunction with contention-based access protocols, such as CSMA/CA (Carrier Sense Multiple Access/Collision Avoidance). Energy consumption is one of the most important issues in WPAN systems, because WPAN devices are often required to operate under limited battery capacity. Furthermore, if the WPAN adopts a contention-based medium access protocol, the energy consumption problem becomes even more critical due to the collisions caused by independent channel access trials. Therefore, in this paper, we propose an algorithm that selects the optimum fragment size, modulation level, and transmission power, in order to minimize the energy consumption and guarantee the QoS (Quality of Service) requirements, simultaneously. Our simulation results show that the proposed algorithm has better performance than the previous ones.

Detection of the existence of a desired user is considered in this paper. We assume that the signal to noise ratio is high enough to ignore the effects of noise compared with those of the interference by other users. The inter-user interference and user signals are modeled by the Nakagami model. The observation model for this situation is proposed, the locally optimum test statistic is derived under the model, and the asymptotic performance of the test statistic is compared with that of the envelope detector. We show that the locally optimum detector has performance better than the conventional envelope detector.