Published papers

In this paper, coordinated multi-point transmission (CoMP) with attribution macro cell switching in distributed antenna transmission is proposed. The proposed scheme is applied to a macro cell system in which each macro cell consists of multiple micro cells. In the proposed scheme, macro cells can be expanded and overlapped with each other, and each micro cell may switch its attribution macro cell. Inter-cell interference is mitigated in conjunction with CoMP transmission. Numerical results obtained through computer simulation show that the largest improvement in a system throughput is realized with three user equipments per macro cell when an inter-antenna distance is 50 meters. The switching frequency corresponds to the amount of the improvement in the throughput. The switching happens less frequently with a longer inter-antenna distance. Thus, the proposed scheme improves the system throughput than the conventional scheme in a dense distributed antenna system.

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. In the proposed scheme, MRC is applied 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 the improvement of 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 are about 0.5 dB better than those of the conventional BP with MMSE pre-cancellation at a BER of 10-3.

This paper proposes a new index modulation (IM) scheme for a multi-carrier system, in which spreading codes are selected by index bits. In the proposed scheme OFDM transmission is carried out without spreading codes on some of the subcarriers. At the same time, IM with spreading codes is applied. One of the spreading codes corresponding to index bits is selected in each subcarrier, and the selected code is modulated with assigned coding bits. By increasing the number of coding bits transmitted at a time, the coding rate of the system is reduced, and the overall performance is improved. The OFDM signal and the spreading signal by IM co-exists and interfere with each other. At a receiver, soft replica symbols are generated from the soft output of a demodulator or a decoder and subtracted from the received signal to cancel the interference. Numerical results obtained through computer simulation results show the performance improvement of about 3.0 dB at a bit error rate of 10-4 compared with the conventional multicarrier transmission and 6-path Rayleigh fading channels.

In this paper, a nonlinear quantized precoding 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 precoding scheme that optimizes individual transmit antenna gains as well as the DAC outputs is proposed. In the proposed scheme, the subarray of massive MIMO antennas is treated virtually as a single antenna element. Numerical results obtained through computer simulation show that the proposed precoding scheme achieves bit error rate performance close to that of the conventional precoding scheme with much smaller antenna gains on a CDL-A channel.

This paper proposes an adaptive mixing probability scheme for mixed Gibbs sampling (MGS) or MGS with maximum ratio combining (MRC) in multiple-input multiple-output (MIMO) demodulation. In the conventional MGS algorithm, the mixing probability is fixed. Thus, if a search point is captured by a local minimum, it takes a larger number of samples to escape. In the proposed scheme, the mixing probability is increased when a candidate transmit symbol vector is captured by a local minimum. Using the adaptive mixing probability, the numbers of candidate transmit symbol vectors searched by demodulation algorithms increase. The proposed scheme in MGS as well as MGS with MRC reduces an error floor level as compared with the conventional scheme. Numerical results obtained through computer simulation show that the bit error rates of the MGS as well as the MGS with MRC reduces by about 1/100 when the number of iterations is 100 in a 64×64 MIMO system.

One of the key technologies for the fifth-generation (5G) mobile communication system is massive multiple-input multiple-output (MIMO) that applies beamforming in order to effectively compensate for large propagation losses in high frequency bands and enable the spatial multiplexing of a large number of signal streams over multiple users. To further improve a system throughput, a coordinated cluster system in which a large number of massive MIMO base stations are deployed in high density has been investigated. The dense deployment greatly improves the system capacity by controlling base stations from a centralized base band unit. However, when clusters are closely located in order to serve densely populated areas, inter-beam interference between adjacent clusters becomes more severe. To suppress the interference to adjacent clusters, only a simple beam switch control scheme at a cluster boundary has been investigated as a conventional scheme. In this paper, the scheduling algorithm for massive MIMO downlink transmission near cluster boundaries, which combines two scheduling algorithms, has been proposed. In the proposed scheme, each base station divides its own cell to multiple areas, switches supporting areas sequentially, and serves users in those areas. The numerical results show that the throughputs improve with a little reduction in a fairness index (FI) when the number of users per resource block is one. The FI reaches the highest when the number of users per cell is equal to the number of divided areas. The proposed scheme reduces computational complexity as compared with those of conventional two schemes.

In this paper, the application of minimum mean square error (MMSE) pre-cancellation prior to belief propagation (BP) is proposed as a detection scheme for overloaded multiple-input multiple-output (MIMO). In overloaded MIMO, the loops in a factor graph deteriorate the demodulation performance with BP. Therefore, the proposed scheme applies the MMSE pre-cancellation prior to BP and reduces the number of the loops. Furthermore, it is applied to the selected transmit and receive nodes so that the condition number of an inverse matrix in the MMSE weight matrix is minimized in order to suppress the residual interference and the noise after the MMSE precancellation. It is shown by numerical results obtained through computer simulation that the proposed scheme achieves better bit error rate (BER) performance than BP without the MMSE pre-cancellation. The proposed scheme improves the BER performance by 4.6-5.0 dB at a BER of 5.0 × 10-3 as compared with conventional BP. Numerical results also shows that the MMSE pre-cancellation reduces the complexity in BP by a factor of 1/896 in terms of the number of multiplication operations.

One of key technologies in the fifth generation mobile communications is a distributed antenna system (DAS). As DAS creates tightly packed antenna arrangements, inter-user interference degrades its spectrum efficiency. Round-robin (RR) scheduling is known as a scheme that achieves a good trade-off between computational complexity and spectrum efficiency. This paper proposes a user equipment (UE) allocation scheme for RR scheduling. The proposed scheme offers low complexity as the phase of UE allocation sequences are predetermined. Four different phase selection criteria are compared in this paper. Numerical results obtained through computer simulation show that maximum selection, which sequentially searches for the phase with the maximum tentative throughput realizes the best spectrum efficiency next to full search. There is an optimum number of UEs which obtains the largest throughput in single-user allocation while the system throughput improves as the number of UEs increases in 2-user RR scheduling.

This letter proposes a frequency domain equalization (FDE) scheme with a threshold in molecular communication (MC). The responses of a MC channel are tendency to have low pass characteristics and inter-symbol interference limits the data rates of MC. However, because of the characteristics of the MC channel, equalization coefficients for high frequency components may increase. Therefore, noise enhancement occurs and it deteriorates communication performance. As large channel responses concentrate at around a zero-frequency component, in the proposed equalization scheme, the high frequency component of the received signal is eliminated if the equalization coefficient exceeds a threshold in the proposed scheme. Numerical results obtained through computer simulation show that the threshold improves the communication performance with the proposed FDE. It is also shown that the trade-off between the noise enhancement and the pulse waveform effects on the performance.

This letter proposes approximated zero forcing precoding with a threshold in molecular communication (MC). Frequency domain precoding for channel equalization is investigated. Owing to the restriction of a transmitter in MC the main part of an equalized waveform is extracted and a corresponding rectangular waveform is transmitted. In the proposed equalization scheme, the frequency component of the transmit signal is suppressed if a threshold exceeds the channel coefficient in the proposed scheme. Numerical results obtained through computer simulation show that approximation by a single rectangular waveform achieves almost the same performance as that with rectangular approximation that suppresses inter-symbol interference with the proposed precoding technique.

In a full-digital massive multi-user MIMO system, maximal-ratio combining (MRC) can obtain more considerable diversity gain while inter-stream interference (ISI) and multi-user interference (MUI) can be canceled using minimum mean square error (MMSE) algorithm. This letter evaluates the throughputs of detection schemes for different antenna numbers in the massive MIMO system with low-resolution analog-to-digital converters (ADCs). The letter makes a comparison between MRC and MMSE under quantization range limit. Numerical results show that MRC achieves better system performance with lower implementation complexity as the number of antennas increases.

The sum rate and bit error rate (BER) performance of nonlinier quantized precoding using Gibbs sampling are evaluated in a massive multiuser multiple-input multiple-output (MU-MIMO) system in this paper. Massive MU-MIMO is a key technology to handle the growth of data traffic. In a full digital massive MU-MIMO system, however, the resolution of digital-to-analogue converters (DACs) in transmit antenna branches have to be low to yield acceptable power consumption. Thus, a combinational optimization problem is solved for the nonlinier quantized precoding to determine transmit signals from finite alphabets output from low resolution DACs. A conventional optimization criterion minimizes errors between desired signals and received signals at user equipments (UEs). However, the system sum rate may decrease as it increases the transmit power. This paper proposes two optimization criteria that take the transmit power into account in order to maximize the sum rate. Mixed Gibbs sampling is applied to obtain the suboptimal solution of the nonlinear optimization problem. Numerical results obtained through computer simulations show that the two proposed criteria achieve higher sum rates than the conventional criterion. On the other hand, the sum rate criterion achieves the largest sum rate while it leads to less throughputs than the MMSE criterion on approximately 60% of subcarriers.

In a multiple-input multiple-output (MIMO) system, maximum likelihood detection (MLD) is the best demodulation scheme if no a priori information is available. However, the complexity of MLD increases exponentially with the number of signal streams. Therefore, various demodulation schemes with less complexity have been proposed and some of those schemes show performance close to that of MLD. One kind of those schemes uses a Gibbs sampling (GS) algorithm. GS MIMO detection that combines feedback from turbo decoding has been proposed. In this scheme, the accuracy of GS MIMO detection is improved by feeding back loglikelihood ratios (LLRs) from a turbo decoder. In this paper, GS MIMO detection using only feedback LLRs from a turbo decoder is proposed. Through extrinsic information transfer (EXIT) chart analysis, it is shown that the EXIT curves with and without metrics calculated from received signals overlap as the feedback LLR values increase. Therefore, the proposed scheme calculates the metrics from received signals only for the first GS MIMO detection and the selection probabilities of GS MIMO detection in the following iterations are calculated based only on the LLRs from turbo decoders. Numerical results obtained through computer simulation show that the performance of proposed GS turbo MIMO detection is worse than that of conventional GS turbo MIMO detection when the number of GS iterations is small. However the performance improves as the number of GS iterations increases. When the number of GS iterations is 30 or more, the bit error rate (BER) performance of the proposed scheme is equivalent to that of the conventional scheme. Therefore, the proposed scheme can reduce the computational complexity of selection probability calculation in GS turbo MIMO detection.

In this paper, a macro cell switching scheme for distributed antennas is proposed. In conventional distributed antenna transmission (DAT), the macro cell to which each antenna belongs is fixed. Though a cell-free system has been investigated because of its higher system throughput, the implementation cost of front-hauls can be excessive. To increase the flexibility of resource allocation in the DAT with moderate front-haul complexity, we propose the macro cell switching of distributed antennas (DAs). In the proposed scheme, DAs switch their attribution macro cells depending on the amount of pre-assigned connections. 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 and the distance between DAs are larger.