In this paper, a conventional multiuser space-time line code (MSTLC) transmission scheme is enhanced to a new enhanced MSTLC (EMSTLC). By introducing the balancing factors at receivers’ antennas to adjust the achievable rates among users, the EMSTLC precoder and balancing factors are designed in a unified minimum mean square error framework to maximize either sum rate or rate balancing. Numerical results verify that the proposed EMSTLC systems achieve a higher sum rate and better minimum user rate than baseline multiuser transmission methods, including the conventional MSTLC scheme. Furthermore, the designed low-complexity algorithms can significantly reduce the computational complexity of the EMSTLC system.

Codeword decoding schemes are proposed for the channel quality indicator (CQI) of talk‐around direct communications based on IEEE 802.16.1a that supports public protection and disaster relief operations. Since a CQI payload is encoded by using near‐orthogonal block encoding, a non‐coherent correlation method is employed at the receiver to find the CQI index with maximum correlation. To enhance the decoding performance in high mobility environments, a differential decoding scheme is developed. By combining the correlation method and the differential decoder, a new hybrid decoding scheme is proposed. Since the proposed hybrid decoder uses the correlation approach in slow fading channels and exploits the differential decoding in fast fading channels, its decoding performance is robust to the rate of channel variation. Through theoretical analysis and numerical simulations in direction communication environments, it is shown that the proposed non‐coherent decoders are advantageous than a coherent decoding scheme, and the performance of the proposed non‐coherent decoders is compared for varying channel variation rate.

Radio frequency identification (RFID) technology provides a promising solution to the problem of missing object identification in large-scale systems, such as warehouses and bookstores by employing RFID readers to communicate with numerous RFID tags, each of which is attached to a monitored object. To achieve prompt identification of missing tags/objects, extensive research is carried out while the transmission of expatiatory bits from each tag and the occurrence of substantial tag collisions critically degrade the time efficiency. Therefore, this motivates us to propose ProTaR, a probabilistic tag retardation-based protocol, which addresses the missing tag identification problem in a more time-efficient way than the prior work. Based on an improvement of conventional frame-slotted ALOHA algorithm, ProTaR aims at alleviating the tag collision problem and achieving compact tag transmissions. The novelty of ProTaR is manifested mainly in two aspects. ProTaR leverages a mask at a reader to distill partial bits from 96-bit identifier (ID) of each tag for the characterization of tag uniqueness. In this context, ProTaR averts the transmission of redundant bits from both the tags and reader. A bit vector is constructed by the reader to inform each tag of the transmissions of others. This idea successfully eliminates the tag collisions, and hence makes full utilization of tag responses. Experimental results validate that ProTaR achieves 100% identification accuracy regardless of missing tag ratio. Furthermore, extensive simulations present that ProTaR enables the time efficiency improvement of up to 88% compared with benchmarks while merely degrading the optimum by 15%.

How can we discover interesting patterns from time-evolving high speed data streams? How to analyze the data streams quickly and accurately, with little space overhead? High speed data stream has been receiving increasing attentions due to its wide applications such as sensors, network traffic, social networks, etc. One of the most fundamental tasks in the data stream is to find frequent items; especially, finding recently frequent items has become important in real world applications.

This paper proposes some modifications of the COST 231 Walfisch-Ikegami (WI) model to reflect the information related to building and terrain heights of practical environments. Based on the modified WI model, a dual slope propagation model is developed for small cells with electrical and mechanical tilt. To validate the proposed model, propagation measurements are performed in a metropolitan area using commercially deployed small cells. We suggest a procedure to compute the path loss from measurement data considering transmit antenna beam patterns, and determine the break point for the proposed dual slope model using measurement results. Finally, the proposed model is compared through data analysis with conventional propagation prediction models in terms of root mean square deviation (RMSD).

A limited feedback-based transmit beamforming technique for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) is investigated in time-varying channels. The performance of the system is significantly degraded by outdated feedback information even when the channel varies slowly. To compensate for the impairment in time-varying channels, the optimal transmit beamforming vector for a future channel, which maximizes the expected effective channel gain, is derived by applying the autoregressive (AR) model to the channels. These are obtained at the receiver. Following this, schemes for the selection of beamforming vectors are proposed to reduce the feedback amount. These can effectively reduce the amount of feedback information by utilizing both the frequency and time correlation of transmit beamforming vectors. Simulation results show that the proposed techniques outperform existing schemes in terms of the bit error rate (BER) performance with the same amount of feedback.

This paper proposes an energy-aware distributed topology control (EDTC) algorithm for coverage-time optimization unique to clustering-based heterogeneous sensor networks. The coverage-time is defined as the time until one of cluster heads (CHs) runs out of energy. CHs which are operated by EDTC move virtual picket nodes, indicators that determine the boundaries of cluster regions, for the load-balanced regulation of cluster regions in a distributed manner. Regulation of cluster regions leads the load-balanced energy consumption of CH which is in the region for coverage-time maximization. Through a performance evaluation of EDTC, we show that our algorithm for clustering-based heterogeneous sensor networks achieves desired properties.

Spatial multiplexing with linear precoding is a simple technique to take advantage of the high spectral efficiency provided by multiple-input multiple-output (MIMO) systems, and it can be simply implemented over frequency selective channels by using orthogonal frequency division multiplexing (OFDM). This requires channel state information (CSI) at the transmitter in the form of the precoding matrices for all OFDM subcarriers, which can be achieved using feedback. To reduce the feedback requirements, this paper proposes a new precoding method incorporating quantization of a fraction of precoding matrices followed by a special interpolation at the transmitter. Since the precoding matrices are unitary, a new interpolator is proposed on the space of unitary matrices for which the outputs are also unitary. The parameters of the interpolator are optimized based on a mean square error (MSE) or mutual information criterion. Simulations show that performance near that of complete CSI can be achieved with a reasonable amount of feedback.

Transmit beamforming with receive combining is a simple method for exploiting the significant diversity provided by multiple-input multiple-output (MIMO) systems, and the use of orthogonal frequency division multiplexing (OFDM) enables low complexity implementation of this scheme over frequency selective MIMO channels. This paper proposes a beamforming technique that reduces feedback requirements for optimal beamforming. In the proposed architecture, the receiver sends back quantized versions of select beamforming vectors and the transmitter reconstructs the missing beamforming vectors through interpolation. Since a beamforming vector is phase invariant and has unit norm, a new spherical linear interpolator is proposed that exploits additional parameters for phase rotation. These parameters are determined at the receiver in the sense of maximizing the minimum channel gain or capacity, and sent back to the transmitter along with the quantized beamforming vectors. Simulation results show that the proposed beamforming method requires much less feedback information than optimal beamforming with only slight diversity loss.

A frequency offset compensation method for OFDM-FDMA, that can correct offsets after the DFT via circular convolution, is proposed as an alternative to the direct method that corrects frequency offsets by multiplying the complex exponents of the offset estimates before the DFT. In contrast to the direct method whose complexity increases proportional to the number of users, the computational load of the proposed scheme decreases as the number of users increases. It is shown that the proposed method is simpler to implement than the direct method when the number of users is greater than two. Furthermore, the former can outperform the latter, because a frequency offset compensation for one user after the DFT does not affect the data of other users. Computer simulation results demonstrate the advantage of the proposed method.