Published papers

This paper evaluates the throughput performance of uplink beamforming transmission through terminal collaboration. In the proposed scheme multiple user equipments (UEs) form a group and transmit signals synchronously to enhance the power of a received signal at a base station. The signal transmitted through terminal collaboration is selected according to proportional fairness scheduling. Thus, fairness among UEs is maintained simultaneously with system throughput improvement. Numerical results obtained through computer simulation show that the system throughput grows as the number of UEs in the group increases. It is also shown that the proposed scheme increases the system throughput by about 0.5-1.5 bps/Hz.

This paper proposes user equipment (UE) grouping schemes and evaluates the performance of a scheduling scheme for each formed group in collaborative multiple-input multiple-output (MIMO) reception. In previous research, the criterion for UE grouping and the effects of group scheduling has never been presented. In the UE grouping scheme, two criteria, the base station (BS)-oriented one and the UE-oriented one, are presented. The BS-oriented full search scheme achieves ideal performance though it requires knowledge of the relative positions of all UEs. Therefore, the UE-oriented local search scheme is also proposed. As the scheduling scheme, proportional fairness scheduling is used in resource allocation for each formed group. When the number of total UEs increases, the difference in the number of UEs among groups enlarges. Numerical results obtained through computer simulation show that the throughput per user increases and the fairness among users decreases when the number of UEs in a cell increases in the proposed schemes compared to those of the conventional scheme.

This paper proposes user equipment (UE) grouping schemes that take user fairness into account in collaborative multiple-input multiple-output reception. In previous research, the criterion for UE grouping to improve system throughput is proposed. However, the user fairness is deteriorated if these schemes focus on the system throughput. In this paper, the range of the received signal power is restricted to reduce the difference among user throughput. Numerical results obtained through computer simulation show that there is a trade-off relationship between the user throughput and the user fairness via the range of the received signal power.

In this paper, belief propagation (BP) multi-input multi-output (MIMO) detection with maximum ratio combining (MRC) and minimum mean square error (MMSE) pre-cancellation is proposed for overload MIMO. The proposed scheme applies MRC before MMSE pre-cancellation. The BP MIMO detection with MMSE pre-cancellation leads to a reduction in diversity gain due to the decreased number of connections between variable nodes and observation nodes in a factor graph. MRC increases the diversity gain and contributes to improve bit error rate (BER) performance. Numerical results obtained through computer simulation show that the BERs of the proposed BP MIMO detection with MRC and MMSE pre-cancellation yields bit error rates (BERs) that are approximately 0.5dB better than those of conventional BP MIMO detection with MMSE pre-cancellation at a BER of 10-3.

In this paper multi-user signal reception with an unmanned ariel vehicle (UAV) relay station (RS) in an uplink heterogeneous network is proposed. In a conventional heterogeneous network cooperative signal reception between a UAV RS and a macro base station (BS) has rarely investigated. Therefore, in this paper, minimum mean square error (MMSE) multi-user signal detection with the UAV RS and the macro BS is applied to improve a system throughput. In the proposed scheme, the UAV RS works as an amplify-and-forward relay station. The link between the UAV RS and the macro BS is assumed to be connected through a millimeter wave link. Numerical results obtained enough computer simulation show that the throughputs of both users supported by the UAV RS and the macro BS improve and a fairness index between users increases.

This paper proposes a minimum mean square error (MMSE) equalization-based multi-input multi-output (MIMO) demodulation scheme with Metropolis-Hastings random walk along a gradient descent direction. The conventional scheme using intermediate search points works effectively for higherorder modulation symbols. However, its performance is deteriorated for lower-order modulation symbols. The proposed scheme suppresses the coefficients in the offdiagonal components of a channel matrix by applying MMSE equalization and improves performance in low signal-to-noise power ratio conditions even for lowerorder modulation symbols. Numerical results obtained thorough computer simulation show that the proposed scheme improves by about 2.0 dB at a bit error rate of 10-2 when the number of iteraitons is 10 for QPSK symbols with 64 transmit and receive antennas.

This paper proposes the affiliation macrocell switching of picocells in a distributed antenna system (DAS). In a conventional DAS, a macrocell is composed of a fixed number of picocells. On the other hand, in the proposed scheme, picocells can switch their affiliation to adjacent macrocells so that the throughputs of cell-edge users improve. The proposed scheme aims to improve a system throughput with the moderate increase of backhaul complexity. Numerical results obtained through computer simulation show that the proposed scheme improves the system throughput by approximately 0.3 bps/Hz/cell and maintains user fairness. Moreover, the system throughput improves regardless of the distance between distributed antennas.

The resource allocation in high throughput satellites (HTSs) has been extensively investigated due to their payload ability to provide high-capacity and high-speed communication. To date, research has been conducted on variable beam arrangement using digital beamforming technology and on illumination patterns using beam hopping. In addition, there has been a great deal of research on flexible frequency resource allocation realized by digital channelizers. However, limited attention has been paid to a coordination of system throughput and fairness among user equipments (UEs) in these previous studies. In our previous paper, we proposed a frequency resource allocation model based on a beam-indexes-series finite Markov decision process. The policies of the resource allocation determined by a network operation center were only focused on maximizing either the number of allocated UEs or the system throughput. In this paper, we introduce a combined evaluation function that considers both the system throughput and the number of allocated UEs. This allows for the simultaneous optimization of communication capacity and fairness of communication opportunities. The superiority of the proposed resource allocation scheme and combined evaluation function is demonstrated through computational simulation in the comparison of the allocation scheme in the prior research. The operator is then able to coordinate the trade-off between system throughput and fairness among UEs.

Channel estimation is required to demodulate the multiple-input multiple-output (MIMO) signals and there are blind and non-blind channel estimation schemes. One of non-blind channel estimation schemes is using Gibbs sampling. In channel estimation using Gibbs sampling, when the number of received data symbols is small, estimation accuracy may be deteriorated owing to the unreliability of weights. In order to solve this problem, this paper introduces a coefficient for adjusting the weights used in channel estimation with Gibbs sampling. When the number of data symbols is small, larger coefficient values are found to be more suitable because they suppress the fluctuation of channel estimation. Numerical results obtained though computer simulation show that the proposed scheme improves by about 5dB as compared with a decision directed scheme in a 4 × 4 MIMO system when the number of data symbols is one.

In this paper, a macro cell switching scheme for distributed antennas is proposed. In conventional distributed antenna transmission (DAT), a macro cell to which each antenna belongs is fixed. Though a cell-free system has been investigated because of its higher system throughput, the complexity of front-haul can be inevitably large. To increase the flexibility of resource allocation in the DAT with moderate front-haul complexity, the macro cell switching of distributed antennas (DAs) is proposed. In the proposed scheme, DAs switch their attribution macro cells depending on the amount of pre-assigned resources. Numerical results obtained through computer simulation show that the proposed scheme realizes a better system throughput than the conventional system especially when the number of user equipments (UEs) is smaller.

In this paper, two-stage BP detection is proposed for overloaded MIMO. In the two-stage BP detection scheme, the BP with MMSE pre-cancellation algorithm followed by the normal BP detection is applied. In overloaded MIMO systems, the loops in a factor graph degrade the demodulation performance of BP detection. MMSE pre-cancellation reduces the number of connections or coefficient values in the factor graph and improves the convergence characteristics of posteriori probabilities. Numerical results obtained through computer simulation have shown that the BERs of the proposed two-stage BP detection are about 1.0-1.5dB better than those of the conventional BP with MMSE pre-cancellation when the MMSE block size is four and the number of MMSE blocks is one.

In this paper, erasure demodulation for an M-ary chirp spread spectrum signal is proposed. This demodulation scheme is assumed to be implemented in IoT devices to receive a deactivation command. In the erasure demodulation scheme a demodulator regards bit elements in a coded bit sequence as erasure if the corresponding correlator output is larger than a threshold and they are different from bit elements in a coded bit sequence for the maximum correlator output. Those erasure bits are treated as both "0"and "1"and cyclic redundancy check (CRC) decoding following the erasure demodulation checks which output is correct. As one of those outputs must be the same as the transmit coded bit, block error rate (BLER) performance improves. Even though the erasure demodulation increases the probability of false alarm, it can reduce the miss probability of deactivation. On the other hand, as the number of erasure bits increases, the number of CRC decoding operations grows exponentially and the probability of CRC miss detection also increases. Thus, the threshold level has to be decided according to the computational capability of each IoT device, the target BLER, and the probability of CRC miss detection. The performance of CRC miss detection and the BLER on a Rayleigh fading channel, a Rician fading channel, and a Vehicular-B channel are evaluated through computer simulation. Furthermore, cumulative distribution function curves for the number of erasure bits are also presented for different channel models.

In this paper, a non-linear precoding algorithm with low out-of-band (OOB) radiation in a massive multiple-input multiple-output (MIMO) system is proposed. Massive MIMO is a system with more than a few hundred antennas implemented in a base station and is characterized by better spectral efficiency and higher throughput. Full digital massive MIMO may require lower resolution in digital-to-analog converters (DACs) since each high-resolution DAC consumes a large amount of power. In massive MIMO systems with low resolution DACs, an output signal designed by nonlinear processing has been investigated. The conventional scheme focuses only on a sum rate or errors in received signals and causes large OOB radiation. This paper proposes an optimization criterion that takes OOB radiation power into account. Gibbs sampling is used as an algorithm to search for a sub-optimal solution for this criterion. Numerical results obtained through computer simulation show that the proposed criterion reduces the mean OOB radiation power by a factor of 10 as compared with the conventional criteria. Furthermore, the proposed criterion achieves larger sum rate over all subcarriers as compared with an error based criterion. On the other hand, as compared with a sum rate based criterion, the throughput on each subcarrier shows less variation and that demands a smaller number of link adaptation options although the average sum rate of the proposed criterion is smaller.

In this paper, user set elimination in the allocation sequences of round-robin (RR) scheduling for distributed antenna transmission (DAT) is proposed. In prior research, the initial phase selection of the user equipment (UE) allocation sequences in RR scheduling has been investigated. However, all of UE sets are included without taking their throughputs into account. Thus, a UE set is assigned even through its total throughput is the lowest. The proposed scheme eliminates the specific UE sets from the RR scheduling sequence according to the expected total throughput of those UE sets. In addition, the initial phase selection is applied to the remaining UE sets. Numerical results obtained through computer simulation show that fairness index as well as system throughput improve when the ratio of eliminated UE sets is small.

In this paper, belief propagation (BP) multiple-input multiple-output (MIMO) detection with minimum mean square error (MMSE) pre-cancellation matrix switching in overloaded MIMO systems is proposed. Loops in a factor graph degrades the demodulation performance of the BP scheme. Therefore, several schemes that suppresses the negative impact of loopy BP have been proposed. Among them, the application of MMSE pre-cancellation prior to BP has been proposed. In the scheme, the effects of loops in the factor graph is suppressed by MMSE pre-cancellation. However, many loops with large coefficients remain in the factor graph even after MMSE pre-cancellation. Therefore, the proposed scheme applies MMSE pre-cancellation matrix switching every after a preset number of BP iterations in order to suppress the occurrence of large beliefs in the loops. Numerical results obtained through computer simulation show that the proposed scheme achieves better BER performance than BP with MMSE pre-cancellation without matrix switching. The proposed scheme outperforms the conventional without switching by 0.7 dB at BER= 10-3.

In this paper, we propose a cell-free distributed antenna system (DAS) architecture with adaptive resolution-(AR-) analog-to-digital converters (ADCs) in access points (APs). The proposed scheme adopts accurate models of the combined effects of clipping, quantization, and thermal noise in the ADC to analyze the quantization characteristics with different resolutions at different received signal-to-interference-and-noise ratios (SINRs). The proposed resolution bit selection criterion of the AR-ADC scheme is then applied. The AR-ADC scheme is to minimize the ADC resolution bits under allowable quantization distortion, and obtain the corresponding optimal clipping factor of the signal-to-interference-plus-quantization-and-noise ratio (SIQNR) for the desired received signal. The contributions of this paper are as follows; 1) the AR-ADC scheme provides a receiver architecture that realizes better energy efficiency (EE), 2) the spectral efficiency (SE) performance is improved by allocating more resolution bits to the APs closer to each UE with the proposed criterion. Numerical results demonstrate that the proposed AR-ADC scheme improves the EE more than tenfold as compared with the other schemes except the system with only 1-bit ADCs. Moreover, the proposed AR-ADC doubles the SE as compared with the system with only 1-bit ADCs.

In the fifth-generation mobile communication system (5G) mixed numerology is standardized to meet the requirements of various services. In this paper, mixed numerology signal transmission in which multiple signals with different numerologies is assumed. As a conventional pilot signal, demodulation reference signal (DMRS) in a forth generation mobile communication (4G) is applied. However, under mixed numerology non-orthogonal multiple access (NOMA), DMRS can not realize orthogonality between pilot signals. As a solution, new pilot signal design based on a Zadoff-Chu sequence is proposed. The proposed pilot signal assignment scheme improves orthogonality between signals with different numerologies and, as a result, reduces bit error rate (BER) performance. Numerical results obtained through computer simulation show that the proposed pilot signal assignment scheme improves the performance by about 2.0 dB at a BER of 10{-2}.

In this paper, user set selection in the allocation sequences of round-robin (RR) scheduling for distributed antenna transmission with block diagonalization (BD) pre-coding is proposed. In prior research, the initial phase selection of user equipment allocation sequences in RR scheduling has been investigated. The performance of the proposed RR scheduling is inferior to that of proportional fair (PF) scheduling under severe intra-cell interference. In this paper, the multi-input multi-output technology with BD pre-coding is applied. Furthermore, the user equipment (UE) sets in the allocation sequences are eliminated with reinforcement learning. After the modification of a RR allocation sequence, no estimated throughput calculation for UE set selection is required. Numerical results obtained through computer simulation show that the maximum selection, one of the criteria for initial phase selection, outperforms the weighted PF scheduling in a restricted realm in terms of the computational complexity, fairness, and throughput.

In this paper, a nonlinear quantized precoding and gain adjustment scheme for low-resolution digital-analog converters (DACs) in a massive multiple-input multiple-output (MIMO) system is proposed. The nonlinear quantized precoding determines transmit antenna outputs with a transmit symbol and channel state information. In a full-digital massive MIMO system, low-resolution DACs are used to suppress power consumption. Conventional precoding algorithms for low-resolution DACs do not optimize transmit antenna gains individually. Thus, in this paper, a gain adjustment scheme that optimizes individual transmit antenna gains and the DAC outputs of a virtual block antenna formed by multiple antennas is proposed. Numerical results obtained through computer simulation show that the proposed precoding scheme achieves bit error rate performance close to that of the conventional Gibbs sampling based algorithm with much smaller antenna gains on a i.i.d Rayleigh fading channel.