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.

This paper proposes low-complexity blind detection for orthogonal frequency division multiplexing (OFDM) systems with the differential space-time block code (DSTBC) under time-varying frequency-selective Rayleigh fading. The detector employs the maximum likelihood sequence estimation (MLSE) in cooperation with the blind linear prediction (BLP), of which prediction coefficients are determined by the method of Lagrange multipliers. Interpolation of channel frequency responses is also applied to the detector in order to reduce the complexity. A complexity analysis and computer simulations demonstrate that the proposed detector can reduce the complexity to about a half, and that the complexity reduction causes only a loss of 1 dB in average Eb/N0 at BER of 10-3 when the prediction order and the degree of polynomial approximation are 2 and 1, respectively.

This paper proposes a low-complexity signal detection algorithm for spatially correlated multiple-input multiple-output (MIMO) channels. The proposed algorithm sets a minimum mean-square error (MMSE) detection result to the starting point, and searches for signal candidates in multi-dimensions of the noise enhancement from which the MMSE detection suffers. The multi-dimensional search is needed because the number of dominant directions of the noise enhancement is likely to be more than one over the correlated MIMO channels. To reduce the computational complexity of the multi-dimensional search, the proposed algorithm limits the number of signal candidates to O(NT) where NT is the number of transmit antennas and O( ) is big O notation. Specifically, the signal candidates, which are unquantized, are obtained as the solution of a minimization problem under a constraint that a stream of the candidates should be equal to a constellation point. Finally, the detected signal is selected from hard decisions of both the MMSE detection result and unquantized signal candidates on the basis of the log likelihood function. For reducing the complexity of this process, the proposed algorithm decreases the number of calculations of the log likelihood functions for the quantized signal candidates. Computer simulations under a correlated MIMO channel condition demonstrate that the proposed scheme provides an excellent trade-off between BER performance and complexity, and that it is superior to conventional one-dimensional search algorithms in BER performance while requiring less complexity than the conventional algorithms.

This paper proposes a new configuration of the Doherty amplifier by introducing digital signal processing that realizes a high efficiency over a wide range of output power. The configuration includes two branches; one branch has a class AB amplifier as the carrier amplifier and the other has two class B amplifiers in cascade as the peak amplifier. Each branch is directly controlled by the digital signal processing unit. The unit controls input power allocation to each branch by a method derived from equations characterizing the carrier and the peak constituent amplifiers. The method includes the compensation of the amplifier for degradation due to nonlinearities. The output power of each constituent amplifier is adjusted by drain DC biases. Calculated characteristics agree well with those obtained by the measurement of a fabricated proposed amplifier, whose efficiency is higher than that of the conventional class AB power amplifiers. Furthermore, a simulation for the OFDM signal specified by the radio LAN shows that the amplifier has sufficient linearity, and that the efficiency exceeds 20% at the output of 20 dBm.

This paper proposes an OFDM mobile packet transmission scheme that increases throughput by using nonlinear multiuser detection (MUD) and automatic repeat request (ARQ) with metric-combining. The scheme identifies users by detecting user identification (ID) symbols located at the head of a packet, and can separate packets that have collided by using MUD. It also forces the respective transmitters to retransmit the same packets so as to reproduce the collision if the cyclic redundancy check (CRC) detects some errors, and it uses metric-combining to decrease the number of retransmissions. The results of computer simulations show that the proposed scheme can provide twice the throughput of the conventional schemes.

In W-CDMA systems, distributions of the interference power and the total transmit power both measured at base stations are respectively used for capacity analysis in the uplink and downlink. For accurate capacity analysis, these quantities must be in proportion to the traffic amount. However, these quantities are no longer in proportion to the traffic amount since the transmit power control maintains the signal to interference power ratio at a constant level. Although the relationship between these measurements and the traffic amount has been investigated, there are still challenges to calculate the statistics such as the blocking probability or the outage probability accurately. This paper proposes a method to calculate the blocking probability by transforming the distributions of these measurements into distributions that are referred to as "traffic equivalent distributions," where the distributions are automatically adjusted according to the traffic amount. The calculated results show good agreement with the results obtained by dynamic computer simulations in the uplink, and show good agreement in the downlink as well when the traffic load is light. Accurate calculation of the blocking probability using a feedback loop and the observation of the traffic equivalents is also reported.