A novel compact multi-input multi-output (MIMO) antenna system with split-ring resonator (SRR), a popular metamaterial structure, is presented. The MIMO antenna system consists of SRRs as radiator elements arranged close to each other on a printed circuit board. We evaluate the antenna characteristics with a single and two SRR elements arranged within various sizes of area. We also analyze MIMO channel capacities of SRR elements by using radiation patterns. The obtained results confirm that the proposed MIMO antenna system can achieve the same channel capacity as a conventional MIMO antenna system but with a 30% smaller footprint area and is very suitable for compact wireless equipment in next-generation wireless systems.

A simple but efficient method for evaluating the channel capacity of 2×2 multiple-input multiple-output (MIMO) antenna systems is proposed. First, the channel capacity of a half-wavelength dipole array antenna is calculated using the Monte Carlo method by changing the incident-wave signal-to-noise power ratio, the power difference between two elements, and the correlation coefficient. Using the calculated results, a polynomial function is derived by multivariate regression analysis to estimate the channel capacity. The validity of the developed function is confirmed by comparing the channel capacity estimated by the developed function with that calculated by the Monte Carlo method using a MIMO array antenna operated under various scenarios, including antenna-human body electromagnetic interactions and radio-wave propagation environments, for future MIMO systems. The function is also validated by means of two experimental approaches: the use of radiation patterns measured in an anechoic chamber and the use of a spatial fading emulator that can create a two-dimensional fading environment.

The online unit clustering problem is one of the most basic clustering problems proposed by Chan and Zarrabi-Zadeh (WAOA2007 and Theory of Computing Systems 45(3), 2009). Several variants of this problem have been extensively studied. In this letter, we propose a new variant of the online unit clustering problem, called the online unit clustering problem with capacity constraints. For this problem, we use competitive analysis to evaluate the performance of an online algorithm. Then, we develop an online algorithm whose competitive ratio is at most 3.178, and show that a lower bound on the competitive ratio of any online algorithm is 2.

This letter considers a cognitive radio (CR) network where multiple secondary downlinks coexist with a primary network. The primary user (PU) is assumed to be protected by the interference outage constraint with only channel distribution information (CDI) being available at the secondary users (SUs). The power allocation problem to maximize the sum outage capacity of the SUs under the interference outage constraint and the transmit power constraint is investigated. Due to the difficulty in obtaining the optimal solution, we propose a heuristic power allocation algorithm based on the bisection search method that can guarantee to satisfy both the interference outage and the transmit power constraints. It is shown that the proposed algorithm converges fast and outperforms other reference algorithms.

Write once memory (WOM) codes allow reuse of a write-once medium. This paper focuses on applying WOM codes to the binary symmetric asymmetric multiple access channel (BS-AMAC). At one specific rate pair, WOM codes can achieve the BS-AMAC maximum sum-rate. Further, any achievable rate pair for a two-write WOM code is also an achievable rate pair for the BS-AMAC. Compared to the uniform input distribution of linear codes, the non-uniform WOM input distribution is helpful for a BS-AMAC. In addition, WOM codes enable “symbol-wise estimation”, resulting in the decomposition to two distinct channels. This scheme does not achieve the BS-AMAC maximum sum-rate if the channel has errors, however leads to reduced-complexity decoding by enabling independent decoding of two codewords. Achievable rates for this decomposed system are also given. The AMAC has practical application to the relay channel and we briefly discuss the relay channel with block Markov encoding using WOM codes. This scheme may be effective for cooperative wireless communications despite the fact that WOM codes are designed for data storage.

In this paper, we propose and analyze the opportunistic amplify-and-forward (AF) relaying scheme using antenna selection in conjunction with different adaptive transmission techniques over Rayleigh fading channels. In this scheme, the best antenna of a source and the best relay are selected for communication between the source and destination. Closed-form expressions for the outage probability and average symbol error rate (SER) are derived to confirm that increasing the number of antennas is the best option as compared with increasing the number of relays. We also obtain closed-form expressions for the average channel capacity under three different adaptive transmission techniques: 1) optimal power and rate adaptation; 2) constant power with optimal rate adaptation; and 3) channel inversion with a fixed rate. The channel capacity performance of the considered adaptive transmission techniques is evaluated and compared with a different number of relays and various antennas configurations for each adaptive technique. Our derived analytical results are verified through extensive Monte Carlo simulations.

In a network with dense deployment of multiple-input multiple-output (MIMO) small cells, coverage overlap between the small cells produces intercell-interference, which degrades system capacity. This paper proposes an intercell-interference management (IIM) scheme that aims to maximize system capacity by using both power control for intercell-interference coordination (ICIC) on the transmitter side and interference cancellation (IC) on the receiver side. The power control determines transmit power levels at the base stations (BSs) by employing a neural network (NN) algorithm over the backhaul. To further improve the signal to interference plus noise ratio (SINR), every user terminal (UT) employs a multiuser detector (MUD) as IC. The MUD detects not only the desired signals, but also some interfering signals to be cancelled from received signals. The receiver structure consists of branch metric generators (BMGs) and MUD. BMGs suppress residual interference and noise in the received signals by whitening matched filters (WMFs), and then generate metrices by using the WMFs' outputs and symbol candidates that the MUD provides. On the basis of the metrices, the MUD detects both the selected interfering signals and the desired signals. In addition, the MUD determines which interfering signals are detected by an SINR based replica selection algorithm. Computer simulations demonstrate that the SINR based replica selection algorithm, which is combined with channel encoders and packet interleavers, can significantly improve the system bit error rate (BER) and that combining IC at the receiver with NN power control at the transmitter can considerably increase the system capacity. Furthermore, it is shown that choosing the detected interfering signals by the replica selection algorithm can obtain system capacity with comparable loss and less computational complexity compared to the conventional greedy algorithm.

In the near future, many sensors and terminals will be connected to the public network to provide various convenient IoT/M2M services. In order to connect many sensors to the network efficiently, wireless communication systems in the 920MHz band are seen as attractive solutions. We are focusing on the 920MHz band to research and develop high-capacity protocols that can accommodate many terminals, and low power consumption technologies for battery-driven terminals. In this paper, we describe the following three concrete wireless systems that use our proposals. (1) A physical distribution pallet management system that can handle thousands of pallet-embedded sensors and a wireless module with a battery lifetime of about ten years. (2) Water leakage monitoring system for underground pipes by using sensors and a wireless module in each valve box. (3) A wide-area and high-capacity radio relay system for smart metering services like the reading of gas meters. The radio relay system can accommodate various sensors and terminals and has large potential for providing various IoT/M2M services in conjunction with smart metering services.

The problem of power allocation in maximizing the energy efficiency of the secondary user (SU) in a delay quality-of-service (QoS) constrained CR network is investigated in this paper. The average interference power constraint is used to protect the transmission of the primary user (SU). The energy efficiency is expressed as the ratio of the effective capacity to the total power consumption. By using non-linear fractional programming and convex optimization theory, we develop an energy efficiency power allocation scheme based on the Dinkelbach method and the Lagrange multiplier method. Numerical results show that the proposed scheme outperforms the existing schemes, in terms of energy efficiency.

A method for increasing alignment tolerance in simple multiple-stream transmission is described. Its use of π-shifted antenna directivity phase enables it to cancel interference even when antenna placement deviations occur. The interference cancellation by using π-shifted directivities provides higher alignment tolerance than that with conventional fixed weight methods. It also provides smaller channel gain variation than can be obtained using fixed weights even when antenna displacement occurs. An objective function is described that is determined by the alignment tolerance. The function is defined to maximize the alignment tolerance. The method's validity is confirmed by an experimental analysis of two-stream transmission in which the alignment tolerance of the proposed method is compared to that of conventional fixed weight methods.

Fast proliferation of mobile Internet and high-demand mobile applications necessitates the introduction of different priority classes in next-generation cellular networks. This is especially crucial for efficient use of radio resources in the heterogeneous and virtualized network environments. Despite the fact that many analytical tools have been proposed for capacity and radio resource modelling in cellular networks, only a few of them explicitly incorporate priorities among services. We propose a novel analytical model to analyse the performance of a priority-based cellular CDMA system with finite source population. When the cell load is above a certain level, low-priority calls may be blocked to preserve the quality of service of high-priority calls. The proposed model leads to an efficient closed-form solution that enables fast and very accurate calculation of resource occupancy of the CDMA system and call blocking probabilities, for different services and many priority classes. To achieve them, the system is modelled as a continuous-time Markov chain. We evaluate the accuracy of the proposed analytical model by means of computer simulations and find that the introduced approximation errors are negligible.

The random deployment of small cell base stations (BSs) causes the coverage areas of neighboring cells to overlap, which increases intercell interference and degrades the system capacity. This paper proposes a new intercell interference management (IIM) scheme to improve the system capacity in multiple-input multiple-output (MIMO) small cell networks. The proposed IIM scheme consists of both an interference cancellation (IC) technique on the receiver side, and a neural network (NN) based power control algorithm for intercell interference coordination (ICIC) on the transmitter side. In order to improve the system capacity, the NN power control optimizes downlink transmit power while IC eliminates interfering signals from received signals. Computer simulations compare the system capacity of the MIMO network with several ICIC algorithms: the NN, the greedy search, the belief propagation (BP), the distributed pricing (DP), and the maximum power, all of which can be combined with IC reception. Furthermore, this paper investigates the application of a multi-layered NN structure called deep learning and its pre-training scheme, into the mobile communication field. It is shown that the performance of NN is better than that of BP and very close to that of greedy search. The low complexity of the NN algorithm makes it suitable for IIM. It is also demonstrated that combining IC and sectorization of BSs acquires high capacity gain owing to reduced interference.

Multiple-input multiple-output (MIMO) technology is a useful means of achieving the higher data rates needed in the latest wireless devices. However, weighting calculations for MIMO transmission become complicated when there are a large number of antennas. Thus, developing a simpler way to transmit and receive multiple streams is an idea worth considering. With this in mind, we propose a spatial division method using orthogonal directivities formed by using higher order modes of rectangular microstrip antennas. Each of them is formed by one antenna element so that channels are orthogonalized only by antennas. We verify antenna radiation characteristics by using higher order mode microstrip antennas and confirm that orthogonal directivities are obtained with them. Measurement of two stream transmission reveals that the method achieves almost the same channel capacity as that of an eigenmode-beamforming method because of the high multiplexing gain it achieves.

In this paper, a method of calculating the mean channel capacity based on S-parameter of MIMO (Multiple-Input Multiple-Output) antenna is proposed. This method exploits the correlation matrix calculated from the antenna S-parameter matrix, and offers highly accurate estimates of the mean channel capacity without dependence on SNR (Signal-to-Noise Ratio). The numerical and experimental results revealed that the proposed method can calculate the channel capacity with fair accuracy independent of the number and spacing of the antenna elements if the radiation efficiency is sufficiently high.

Ultra-wideband (UWB) beamforming is now attracting significant research attention for attaining spatial gain from array antennas. It is commonly believed that directional antenna based communication could improve the system performance. In order to further make clear the relationship between system performance and the antenna array beamforming, UWB indoor channels are extracted from practical measurements and circular horn antenna is used to characterize the channel properties and to evaluate the system performance. Using a single beam directional antenna with a certain half power beamwidth (HPBW), the channel capacity and the bit-error-rate (BER) performance of a UWB RAKE receiver are evaluated. In the line-of-sight (LOS) environments, the channel capacity and BER performance are improved with the beamwidth becoming smaller. However in the non-line-of-sight (NLOS) environments, the capacity and BER performance are not always better with directional antennas. And the variation trend between the system performance and the antenna beamwidth disappears. This is mainly because that there exist no dominant strong path components like those seen in LOS environments. Then beam combining is introduced to further improve the system performance. Simulation results show that the channel capacity and BER performance cloud be greatly improved by multiple beam combining, especially for the NLOS environments. This reminds us that when antenna beamforming is used to obtain array gain, the beamwidth should be carefully designed and beam combining is necessary to obtain optimal performance, especially in NLOS environments.

In this paper, we present a weighted-polarization wearable multiple-input multiple-output (MIMO) antenna that is based on radio-frequency (RF) signal processing to realize ultra-high-speed and high-capacity mobile communications. The proposed antenna is comprised of three orthogonal dipoles, two of which can be selected according to a weight function in different usage scenarios. The weight function is determined by considering the variation in the cross-polarization power ratio (XPR) and the antenna inclination angle which depend on the radio-propagation environment and human motion. To confirm the suitability of the proposed antenna, we perform preliminary experiments to evaluate the channel capacity of a weighted-polarization wearable MIMO antenna with an arm-swinging dynamic phantom. The measured and analytical results are in good agreement, which verifies the effectiveness of the proposed antenna. We demonstrate that the proposed antenna is suitable for realizing gigabit mobile communications in future wearable MIMO applications.

This paper analyzes the impact of directional antennas in improving the transmission capacity, defined as the maximum allowable spatial node density of successful transmissions multiplied by their data rate with a given outage constraint, in wireless networks. We consider the case where the gain Gm for the mainlobe of beamwidth can scale at an arbitrarily large rate. Under the beamwidth scaling model, the transmission capacity is analyzed for all path-loss attenuation regimes for the following two network configurations. In dense networks, in which the spatial node density increases with the antenna gain Gm, the transmission capacity scales as Gm4/α, where α denotes the path-loss exponent. On the other hand, in extended networks of fixed node density, the transmission capacity scales logarithmically in Gm. For comparison, we also show an ideal antenna model where there is no sidelobe beam. In addition, computer simulations are performed, which show trends consistent with our analytical behaviors. Our analysis sheds light on a new understanding of the fundamental limit of outage-constrained ad hoc networks operating in the directional mode.

This paper proposes a new method that combines signal modulation and FDTD (Finite-Difference Time-Domain) simulations to reduce the computation time in multiple-antenna analysis. In this method, signals are modulated so as to maintain orthogonality among the excited signals; multiple antennas are excited at the same time. This means just one FDTD simulation is needed whereas the conventional method demands as many simulations as there are transmitting antennas. The simulation of a 2×2 multi-antenna system shows that the proposed method matches the performance of the conventional method even though its computation time is much shorter.

The dramatic growth in wireless data traffic has triggered the investigation of fifth generation (5G) wireless communication systems. Small cells will play a very important role in 5G to meet the 5G requirements in spectral efficiency, energy savings, etc. In this paper, we investigate low complexity millimeter-wave communication systems with uniform circular arrays (UCAs) in line-of-sight (LOS) multiple-input multiple-output (MIMO) channels, which are used in fixed wireless access such as small cell wireless backhaul for 5G. First, we demonstrate that the MIMO channel matrices for UCAs in LOS-MIMO channels are circulant matrices. Next, we provide a detailed derivation of the unified optimal antenna placement which makes MIMO channel matrices orthogonal for 3×3 and 4×4 UCAs in LOS channels. We also derive simple analytical expressions of eigenvalues and capacity as a function of array design (link range and array diameters) for the concerned systems. Finally, based on the properties of circulant matrices, we propose a high performance low complexity LOS-MIMO precoding system that combines forward error correction (FEC) codes and spatial interleaver with the fixed IDFT precoding matrix. The proposed precoding system for UCAs does not require the channel knowledge for estimating the precoding matrix at the transmitter under the LOS condition, since the channel matrices are circulant ones for UCAs. Simulation results show that the proposed low complexity system is robust to various link ranges and can attain excellent performance in strong LOS environments and channel estimation errors.

The problem of power allocation for the secondary user (SU) in a cognitive radio (CR) network is investigated in this paper. The primary user (PU) is protected by the average interference power constraint. Besides the average interference power constraint at the PU, the transmit power of the SU is also subject to the peak or average transmit power constraint. The aim is to balance between the goal of maximizing the ergodic capacity and the goal of minimizing the outage probability of the SU. Power allocation schemes are then proposed under the aforementioned setups. It is shown that the proposed power allocation schemes can achieve high ergodic capacity while maintaining low outage probability, whereas existing schemes achieve either high ergodic capacity with high outage probability or low outage probability with low ergodic capacity.