In this paper, we investigate optimal design of millimeter-wave (mmWave) multiuser line-of-sight multiple-input-multiple-output (LOS MIMO) systems using hybrid arrays of subarrays based on hybrid block diagonalization (BD) precoding and combining scheme. By introducing a general 3D geometric channel model, the optimal subarray separation products of the transmitter and receiver for maximizing sum-rate is designed in terms of two regular configurations of adjacent subarrays and interleaved subarrays for different users, respectively. We analyze the sensitivity of the optimal design parameters on performance in terms of a deviation factor, and derive expressions for the eigenvalues of the multiuser equivalent LOS MIMO channel matrix, which are also valid for non-optimal design. Simulation results show that the interleaved subarrays can support longer distance communication than the adjacent subarrays given the appropriate fixed subarray deployment.

In unlicensed spectrum, wireless communications employing carrier sense multiple access with collision avoidance (CSMA/CA) suffer from longer transmission delay time as the number of user terminals (UTs) increases, because packet collisions are more likely to occur. To cope with this problem, this paper proposes a new multiuser detection (MUD) scheme that uses both request-to-send (RTS) and enhanced clear-to-send (eCTS) for high-reliable and low-latency wireless communications. As in conventional MUD scheme, the metric-combining MUD (MC-MUD) calculates log likelihood functions called metrics and accumulates the metrics for the maximum likelihood detection (MLD). To avoid increasing the number of states for MLD, MC-MUD forces the relevant UTs to retransmit their packets until all the collided packets are correctly detected, which requires a kind of central control and reduces the system throughput. To overcome these drawbacks, the proposed scheme, which is referred to as cancelling MC-MUD (CMC-MUD), deletes replicas of some of the collided packets from the received signals, once the packets are correctly detected during the retransmission. This cancellation enables new UTs to transmit their packets and then performs MLD without increasing the number of states, which improves the system throughput without increasing the complexity. In addition, the proposed scheme adopts RTS and eCTS. One UT that suffers from packet collision transmits RTS before the retransmission. Then, the corresponding access point (AP) transmits eCTS including addresses of the other UTs, which have experienced the same packet collision. To reproduce the same packet collision, these other UTs transmit their packets once they receive the eCTS. Computer simulations under one AP conditions evaluate an average carrier-to-interference ratio (CIR) range in which the proposed scheme is effective, and clarify that the transmission delay time of the proposed scheme is shorter than that of the conventional schemes. In two APs environments that can cause the hidden terminal problem, it is demonstrated that the proposed scheme achieves shorter transmission delay times than the conventional scheme with RTS and conventional CTS.

In this paper, we consider interference suppression for a full-duplex (FD) multiuser system based on single-carrier transmission in frequency-selective channels where a FD base-station (BS) simultaneously communicates with half-duplex (HD) uplink and downlink mobile users. We propose a design method for time-domain filtering where the filters in the BS transmitter suppress inter-symbol interference (ISI) and downlink inter-user interference (IUI); those in the BS receiver, self-interference, ISI, and uplink IUI; and those in the downlink mobile users, co-channel interference (CCI) without the channel state information of the CCI channels. Simulation results indicate that the FD system based on the proposed method outperforms the conventional HD system and FD system based on multicarrier transmission.

Massive multiple-input multiple-output (MIMO) systems are a key promising technology for future broadband cellular networks. The propagation paths within massive MIMO radio channels are often sparse, both in the sub-6GHz frequency band and at millimeter wave frequencies. Herein, we propose a two-layer beamforming scheme for downlink transmission over massive multiuser MIMO sparse beam-space channels. The first layer employs a bipartite graph to dynamically group users in the beam-space domain; the aim is to minimize inter-user interference while significantly reducing the effective channel dimensionality. The second layer performs baseband linear MIMO precoding to maximize spatial multiplexing gain and system throughput. Simulation results demonstrate the proposed two-layer beamforming scheme outperforms other, more conventional algorithms.

This paper investigates receive power control for multiuser inductive power transfer (IPT) systems with a single-frequency coil array. The primary task is to optimize the transmit coil currents to minimize the total input power, subject to the minimum receive powers required by individual users. Due to the complicated coupling mechanism among all transmit coils and user pickups, the optimization problem is a non-convex quadratically constrained quadratic program (QCQP), which is analytically intractable. This paper solves the problem by applying the semidefinite relaxation (SDR) technique and evaluates the performance by full-wave electromagnetic simulations. Our results show that a single-frequency coil array is capable of power control for various multiuser scenarios, assuming that the number of transmit coils is greater than or equal to the number of users and the transmission conditions for individual users are uncorrelated.

Multiuser MIMO (MU-MIMO) improves the system channel capacity by generating a large virtual MIMO channel between a base station and multiple user terminals (UTs) with effective utilization of wireless resources. Block beamforming algorithms such as Block Diagonalization (BD) and Block Maximum Signal-to-Noise ratio (BMSN) have been proposed in order to realize MU-MIMO broadcast transmission. The BD algorithm cancels inter-user interference (IUI) by creating the weights so that the channel matrices for the other users are set to be zero matrices. The BMSN algorithm has a function of maintaining a high gain response for each desired user in addition to IUI cancellation. Therefore, the BMSN algorithm generally outperforms the BD algorithm. However, when the number of transmit antennas is equal to the total number of receive antennas, the transmission rate by both BD and BMSN algorithms is decreased. This is because the eigenvalues of channel matrices are too small to support data transmission. To resolve the issue, this paper focuses on an antenna selection (AS) method at the UTs. The AS method reduces the number of pattern nulls for the other users except an intended user in the BD and BMSN algorithms. It is verified via bit error rate (BER) evaluation that the AS method is effective in the BD and BMSN algorithms, especially, when the number of user antennas with a low bit rate (i.e., low signal-to-noise power ratio) is increased. Moreover, this paper evaluates the achievable bit rate and throughput including an actual channel state information feedback based on IEEE802.11ac standard. Although the number of equivalent receive antenna is reduced to only one by the AS method when the number of antennas at the UT is two, it is shown that the throughputs by BD and BMSN with the AS method (BD-AS and BMSN-AS) are higher than those by the conventional BD and BMSN algorithms.

This paper proposes a novel access technique that enables uplink multiuser multiple input multiple output (MU-MIMO) access with small overhead in distributed wireless networks. The proposed access technique introduces a probe packet that is sent to all terminals to judge whether they have the right to transmit their signals or not. The probe packet guarantees high quality MU-MIMO signal transmission when a minimum mean square error (MMSE) filter is applied at the access point, which results in high frequency utilization efficiency. Computer simulation reveals that the proposed access achieves more than twice of the capacity obtained by the traditional carrier sense multiple access/collision avoidance (CSMA/CA) with a single user MIMO, when the access point with 5 antennas is surrounded by the terminals with 2 antennas.

Our previous work proposed a semi-blind single antenna interference cancellation scheme to cope with severe inter-cell interference in heterogeneous networks. This paper extends the scheme to allow multiple-receive-antenna implementation. It does not require knowledge of the training sequences of interfering signals and can cancel multiple interfering signals irrespective of the number of receive antennas. The proposed scheme applies an enhanced version of the quantized channel approach to suboptimal joint channel estimation and signal detection (JCESD) during the training period in order to blindly estimate channels of the interfering signals, while reducing the computational complexity of optimum JCESD drastically. Different from the previous work, the proposed scheme applies the quantized channel generation and local search at each individual receive antenna so as to estimate transmitted symbol matrices during the training period. Then, joint estimation is newly introduced in order to estimate a channel matrix from the estimated symbol matrices, which operates in the same manner as the expectation maximization (EM) algorithm and considers signals received at all receive antennas. Using the estimated channels, the proposed scheme performs multiuser detection (MUD) during the data period under the maximum likelihood (ML) criterion in order to cancel the interference. Computer simulations with two receive antennas under two-interfering-stream conditions show that the proposed scheme outperforms interference rejection combining (IRC) with perfect channel state information (CSI) and MUD with channels estimated by a conventional scheme based on the generalized Viterbi algorithm, and can achieve almost the same average bit error rate (BER) performance as MUD with channels estimated from sufficiently long training sequences of both the desired stream(s) and the interfering streams, while reducing the computational complexity significantly compared with full search involving all interfering signal candidates during the training period.

This paper presents experimental results of our proposed null-space expansion scheme for multiuser massive multiple-input multiple-output (MIMO) in time varying channels. Multiuser MIMO transmission with the proposed scheme can suppress the inter-user interference (IUI) caused by outdated channel state information (CSI). The excess degrees of freedom (DoFs) of massive MIMO is exploited to perform additional null-steering using past estimated CSI. The signal-to-interference power ratio (SIR) and spectral efficiency performances achieved by the proposed scheme that uses measured CSI is experimentally evaluated. It is confirmed that the proposed scheme shows performance superior to the conventional channel prediction scheme. In addition, IUI can be stably suppressed even in high mobility environments by further increasing the null-space dimension.

This paper studies a simultaneous wireless information and power transfer (SWIPT) system in which the transmitter not only sends data and energy to many types of wireless users, such as multiple information decoding users, multiple hybrid power-splitting users (i.e., users with a power-splitting structure to receive both information and energy), and multiple energy harvesting users, but also prevents information from being intercepted by a passive eavesdropper. The transmitter is equipped with multiple antennas, whereas all users and the eavesdropper are assumed to be equipped with a single antenna. Since the transmitter does not have any channel state information (CSI) about the eavesdropper, artificial noise (AN) power is maximized to mask information as well as to interfere with the eavesdropper as much as possible. The non-convex optimization problem is formulated to minimize the transmit power satisfying all signal-to-interference-plus-noise (SINR) and harvested energy requirements for all users so that the remaining power for generating AN is maximized. With perfect CSI, a semidefinite relaxation (SDR) technique is applied, and the optimal solution is proven to be tight. With imperfect CSI, SDR and a Gaussian randomization algorithm are proposed to find the suboptimal solution. Finally, numerical performance with respect to the maximum SINR at the eavesdropper is determined by a Monte-Carlo simulation to compare the proposed AN scenario with a no-AN scenario, as well as to compare perfect CSI with imperfect CSI.

This paper proposes a novel method of reducing channel state information (CSI) feedback by using transmit antenna selection for downlink multiuser multiple input multiple output (DL-MU-MIMO) transmission in dense distributed antenna systems. It is widely known that DL-MU-MIMO transmission achieves higher total bit-rate by mitigating inter-user interference based on pre-coding techniques. The pre-coding techniques require CSI between access point (AP) and multiple users. However, overhead for CSI acquisition degrades the transmission efficiency of DL-MU-MIMO transmission. In the proposed CSI feedback reduction method, AP first selects the antenna set that maximizes the received power at each user, second it skips the sequence of CSI feedback for users whose signal to interference power ratio is larger than a threshold, and finally it performs DL-MU-MIMO transmission to multiple users by using the selected antenna set. To clarify the proposed method, we evaluate it by computer simulations in an indoor scenario. The results show that the proposed method can offer higher transmission efficiency than the conventional DL-MU-MIMO transmission with the usual CSI feedback method.

In order to cope with severe interference in heterogeneous networks, this paper proposes a semi-blind interference cancellation scheme, which does not require multiple receive antennas or knowledge about training sequences of the interfering signals. The proposed scheme performs joint channel estimation and signal detection (JCESD) during the training period in order to blindly estimate channels of the interfering signals. On the other hand, maximum likelihood detection (MLD), which can be considered the optimum JCESD, must perform channel estimation for all transmitted signal candidates of the interfering signals and must search for the most likely signal candidate. Therefore, MLD incurs a prohibitive amount of computational complexity. To reduce such complexity drastically, the proposed scheme enhances the quantized channel approach, and applies the enhanced version to JCESD. In addition, a recalculation scheme is introduced to avoid inaccurate channel estimates due to local minima. Using the estimated channels, the proposed scheme performs multiuser detection (MUD) of the data sequences in order to cancel the interference. Computer simulations show that the proposed scheme outperforms a conventional scheme based on the Viterbi algorithm, and can achieve almost the same average bit error rate performance as the MUD with channels estimated from sufficiently long training sequences of both the desired signal and the interfering signals, while reducing the computational complexity significantly compared with full search involving all interfering signal candidates during the training period.

High-resolution image and video communication in home networks is highly expected to proliferate with the spread of Wi-Fi devices and the introduction of multiple-input multiple-output (MIMO) systems. This paper proposes a joint transmission and coding scheme for broadcasting high-resolution video streams over multiuser MIMO systems with an eigenbeam-space division multiplexing (E-SDM) technique. Scalable video coding makes it possible to produce the code stream comprised of multiple layers having unequal contribution to image quality. The proposed scheme jointly assigns the data of scalable code streams to subcarriers and spatial streams based on their signal-to-noise ratio (SNR) values in order to transmit visually important data with high reliability. Simulation results show that the proposed scheme surpasses the conventional unequal power allocation (UPA) approach in terms of both peak signal-to-noise ratio (PSNR) of received images and correct decoding probability. PSNR performance of the proposed scheme exceeds 35dB with the probability of over 95% when received SNR is higher than 6dB. The improvement in average PSNR by the proposed scheme compared to the conventional UPA comes up to approx. 20dB at received SNR of 6dB. Furthermore, correct decoding probability reaches 95% when received SNR is greater than 4dB.

To suppress intercell interference for three-cell half-duplex relay systems, joint interference suppression and multiuser detection (MUD) schemes that estimate weight coefficients by the recursive least-squares (RLS) algorithm have been proposed but show much worse bit error rate (BER) performance than maximum likelihood detection (MLD). To improve the BER performance, this paper proposes a joint interference suppression and MUD scheme that estimates the weight coefficients by eigenvalue decomposition. The proposed scheme carries the same advantages as the conventional RLS based schemes; it does not need channel state information (CSI) feedback while incurring much less amount of computational complexity than MLD. In addition, it needs to know only two out of three preambles used in the system. Computer simulations of orthogonal frequency-division multiplexing (OFDM) transmission under three-cell and frequency selective fading conditions are conducted. It is shown that the eigendecomposition-based scheme overwhelmingly outperforms the conventional RLS-based scheme although requiring higher computational complexity.

A novel generalized side-information cancellation (GSIC) precoder is proposed for multiuser multi-input multi-output (MIMO) downlink systems with channel state information at the transmitter. The proposed transceiver involves the following stages. First, a minimum mean square error (MMSE) based channel inversion (MMSE-CI) technique is utilized to suppress multiuser broadcast interference. By using a GSIC technique, it can further reduce the residual multiuser interference and the noise induced by MMSE-CI preprocessing. Next, with a singular value decomposition method, the spatial stream interference of each user is suppressed by the pre-processing and post-processing eigenvector matrices. Finally, the proposed precoder can be extended to joint water filling and diagonal loading methods for performance enhancement. For the correlated MIMO channels, signal subspace and antenna selection methods, incorporating the proposed GSIC precoder, are further designed to maximize the sum rate performance. Simulation results show that the proposed GSIC precoder outperforms the conventional precoders. Besides, simulation results confirm that the proposed GSIC precoder with water filling, diagonal loading, and signal subspace techniques exhibits excellent performance.

This paper experimentally verifies the potential of higher order space division multiplexing in line-of-sight (LOS) channels for multiuser massive MIMO. We previously proposed an inter-user interference (IUI) cancellation scheme and a simplified user scheduling method for Massive Antenna Systems for Wireless Entrance (MAS-WE). In order to verify the effectiveness of the proposed techniques, channel state information (CSI) for a 1×32 SIMO channel is measured in a real propagation environment with simplified test equipment. Evaluations of the measured CSI data confirm the effectiveness of our proposals; they offer good equal gain transmission (EGT) performance, reduced spatial correlation with enlarged angular gap between users, and quite small channel state fluctuation. Link level simulations elucidate that the simple IUI cancellation method is stable in practical conditions. The degradation in symbol error rate with the measured CSI, relative to that yielded by the output of the theoretical LOS channel model, is insignificant.

Massive multiple input multiple output (MIMO) communication system offers high rate transmission and/or support of a large number of users by invoking the power of a large array antenna, but one of its problem is the heavy computational burden required for the design and signal processing. Assuming the utilization of a large array in the transmitter side and much fewer users than the maximum possible value, this paper first presents a subarray based design approach of MIMO system with a low computational load taking into account efficient subarray grouping for the realization of higher performance; a large transmit array is first divided into subarrays based on channel gain or channel correlation, then block diagonalization is applied to each of them, and finally a large array weight is reconstructed by maximal ratio combining (MRC). In addition, the extension of the proposed method to two-stage design is studied in order to support a larger number of users; in the process of reconstruction to a large array, subarrays are again divided into groups, and block diagonalization is applied to those subarray groups. Through computer simulations, it is shown that the both channel gain and correlation based grouping strategies are effective under certain conditions, and that the number of supported users can be increased by two-stage design if certain level of performance degradation is acceptable.

This paper proposes a practical application of Massive MIMO technology, Massive Antenna Systems for Wireless Entrance (MAS-WE), and along with related inter-user interference cancellation (IUIC) and scheduling techniques. MAS-WE, in which the entrance base station (EBS) employs a large number of antennas, can effectively provide high capacity wireless entrance links to a large number of access points (APs) distributed over a wide coverage area. The proposed techniques are simplified to practical implementation; EBS side uses around 100 antenna elements to spatially multiplex more than 16 signal streams. SIR performance is evaluated by system level simulations that consider imperfect channel state information (CSI). The results show that MAS-WE with the proposed techniques can reliably achieve high spectral efficiency with high level space division multiplexing.

This paper proposes a null-space expansion scheme for multiuser massive MIMO transmission in order to suppress inter-user interference (IUI) triggered by the temporal variation of the channel. The downlink multiuser MIMO channel capacity of time varying channels is severely degraded since IUI must be suppressed at the transmitter side by using past estimated channel state information at the transmitter side (CSIT). Massive MIMO has emerged as one of the most promising technologies for further capacity enhancement by increasing the number of base station (BS) antenna elements. Exploiting the excess degrees of freedom (DoFs) inherent in massive MIMO, a BS with the proposed IUI suppression scheme performs multiple null-steering for each UE (User Equipment) antenna element, which expands the null-space dimension. Computer simulations show that the proposed scheme has superior IUI suppression performance to the existing channel prediction scheme in time varying channels.

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.