To deal with the recent explosion of mobile data traffic, heterogeneous cellular networks, in which a large number of small cells are deployed in a macro-cell coverage area, are considered to be a promising approach. However, when a mobile terminal (MT) traveling at a high velocity moves through several small cells in a short period of time, the frequent handovers (HOs) that occur between small cells lead to a deterioration of user quality of experience. To avoid such HO problems, while improving the network capacity in the heterogeneous cellular network, it is effective to introduce an inter-layer HO control policy where MTs traveling at high velocities are connected to the macro-cell layer to reduce the number of HOs and MTs traveling at low velocities or which are stationary are connected to the small-cell layer for offloading traffic from the macro-cells to the small-cells. However, to realize such inter-layer HO control policy in the heterogeneous cellular network, it is crucial to estimate the velocity of each MT. Due to the technological constraints of MT velocity estimation based on the Global Positioning Systems (GPS), we focus on MT velocity estimation algorithms which do not require information provided by GPS. First, we discuss the issues of the existing MT velocity estimation algorithms and then focus on a MT velocity estimation algorithm based on a conventional Doppler spread detection using Fast Fourier Transform (FFT). Since few studies have evaluated Doppler spread based MT velocity estimation techniques for practical communication systems in actual radio propagation environments, we implement the MT velocity estimation algorithm to a Long Term Evolution (LTE) based experimental system, and perform its field experiments. Based on these experimental results we also evaluate the high or low velocity decision accuracy for the inter-layer HO control policy and show that good decision accuracy is achieved in both line-of-sight (LOS) and non-line-of-sight (NLOS) outdoor propagation environment. These results show its feasibility for practical mobile communication systems in actual radio propagation environments.

Non-linear precoding (NLP) scheme for downlink multi-user multiple-input multiple-output (DL-MU-MIMO) transmission has received much attention as a promising technology to achieve high capacity within the limited bandwidths available to radio access systems. In order to minimize the required transmission power for DL-MU-MIMO and achieve high spectrum efficiency, Vector Perturbation (VP) was proposed as an optimal NLP scheme. Unfortunately, the original VP suffers from significant computation complexity in detecting the optimal perturbation vector from an infinite number of the candidates. To reduce the complexity with near transmission performance of VP, several recent studies investigated various efficient NLP schemes based on the concept of Tomlinson-Harashima precoding (THP) that applies successive pre-cancellation of inter-user interference (IUI) and offsets the transmission vector based on a modulo operation. In order to attain transmission performance improvement over the original THP, a previous work proposed Minimum Mean Square Error based THP (MMSE-THP) employing IUI successive pre-cancellation based on MMSE criteria. On the other hand, to improve the transmission performance of MMSE-THP, other previous works proposed Ordered MMSE-THP and Lattice-Reduction-Aided MMSE-THP (LRA MMSE-THP). This paper investigates the further transmission performance improvement of Ordered MMSE-THP and LRA MMSE-THP. This paper starts by proposing an extension of MMSE-THP employing a perturbation vector search (PVS), called PVS MMSE-THP as a novel NLP scheme, where the modulo operation is substituted by PVS and a subtraction operation from the transmit signal vector. Then, it introduces an efficient search algorithm of appropriate perturbation vector based on a depth-first branch-and-bound search for PVS MMSE-THP. Next, it also evaluates the transmission performance of PVS MMSE-THP with the appropriate perturbation vector detected by the efficient search algorithm. Computer simulations quantitatively clarify that PVS MMSE-THP achieves better transmission performance than the conventional NLP schemes. Moreover, it also clarifies that PVS MMSE-THP increases the effect of required transmission power reduction with the number of transmit antennas compared to the conventional NLP schemes.