Masanori Hamamura

Bandwidth efficiency improvement for multi-carrier systems

A novel multi-carrier transmission system named high compaction multi-carrier modulation (HC-MCM) is proposed to improve the spectral efficiency of OFDM. The HC-MCM can arbitrarily overlap the spectra of its subcarriers with an operation for the transmitting signal, whereby a fast transmission rate can easily be achieved. A DFT-based transmitter and receiver, spectral efficiency, the minimum Euclidean distance, and bit-error rate (BER) characteristics are elaborated. As a result, it is shown that a remarkable improvement in spectral efficiency can be obtained by the HC-MCM as the number of subcarriers increases. It is also shown that subcarrier spectra overlapping is sensitive to the minimum Euclidean distance, but large enough in comparison with OFDM under the condition that the transmission rate and the frequency spacing of subcarriers are identical to those in OFDM.

An Improved Proportionate Normalized Least-Mean-Square Algorithm for Broadband Multipath Channel Estimation

To make use of the sparsity property of broadband multipath wireless communication channels, we mathematically propose an lp-norm-constrained proportionate normalized least-mean-square (LP-PNLMS) sparse channel estimation algorithm. A general lp-norm is weighted by the gain matrix and is incorporated into the cost function of the proportionate normalized least-mean-square (PNLMS) algorithm. This integration is equivalent to adding a zero attractor to the iterations, by which the convergence speed and steady-state performance of the inactive taps are significantly improved. Our simulation results demonstrate that the proposed algorithm can effectively improve the estimation performance of the PNLMS-based algorithm for sparse channel estimation applications.

Smooth approximation l(0)-norm constrained affine projection algorithm and its applications in sparse channel estimation.

We propose a smooth approximation l 0-norm constrained affine projection algorithm (SL0-APA) to improve the convergence speed and the steady-state error of affine projection algorithm (APA) for sparse channel estimation. The proposed algorithm ensures improved performance in terms of the convergence speed and the steady-state error via the combination of a smooth approximation l 0-norm (SL0) penalty on the coefficients into the standard APA cost function, which gives rise to a zero attractor that promotes the sparsity of the channel taps in the channel estimation and hence accelerates the convergence speed and reduces the steady-state error when the channel is sparse. The simulation results demonstrate that our proposed SL0-APA is superior to the standard APA and its sparsity-aware algorithms in terms of both the convergence speed and the steady-state behavior in a designated sparse channel. Furthermore, SL0-APA is shown to have smaller steady-state error than the previously proposed sparsity-aware algorithms when the number of nonzero taps in the sparse channel increases.

Bandwidth efficiency of PC-OFDM systems with high compaction multi-carrier modulation

In this paper, we adopt a novel high compaction multi-carrier modulation (HC-MCM) technique to PC-OFDM system, the simulated results show that the bandwidth efficiency and BER of PC-OFDM can be greatly improved by this scheme.

Performance Tradeoff with Adaptive Frame Length and Modulation in Wireless Network

In this paper, we present the results of analysis, which shows that there is much to be gained from variable frame length, different modulations in terms of goodput, range and energy consumption for wireless channel. Using those results, then we obtain three useful rules for the tradeoff with goodput, range and energy consumption with different modulations

Asynchronous, Decentralized DS-CDMA Using Feedback-Controlled Spreading Sequences for Time-Dispersive Channels

We propose a novel asynchronous direct-sequence codedivision multiple access (DS-CDMA) using feedback-controlled spreading sequences (FCSSs) (FCSS/DS-CDMA). At the receiver of FCSS/DS-CDMA, the code-orthogonalizing filter (COF) produces a spreading sequence, and the receiver returns the spreading sequence to the transmitter. Then the transmitter uses the spreading sequence as its updated version. The performance of FCSS/DS-CDMA is evaluated over time-dispersive channels. The results indicate that FCSS/DS-CDMA greatly suppresses both the intersymbol interference (ISI) and multiple access interference (MAI) over time-invariant channels. FCSS/DS-CDMA is applicable to the decentralized multiple access.

Collision Recovery for OFDM System over Wireless Channel

We present an effective method of collision recovery for orthogonal frequency division multiplexing (OFDM)-based communications. For the OFDM system, the modulated message data can be demodulated using the partial time-domain OFDM signal. Therefore, the partial time-domain signal can be adopted to reconstruct the whole OFDM time-domain signal with estimated channel information. This property can be utilized to recover packets from the collisions. Since most collisions are cases in which a long packet collides with a short packet, the collided part is assumed to be short. The simulated results show that the method can recover the two collided packets with a certain probability and can be developed to solve the problem of hidden terminals. This method will dramatically benefit the protocol design of wireless networks, including ad hoc and sensor networks.

Random cognitive radio network performance in Rayleigh-lognormal environment

Recently, considerable research has been focused on the design of random cognitive radio networks because base stations are randomly located in modern cellular networks and also because of an anticipated shortage of spectrum. This study investigates the performance of cognitive radio networks using a stochastic geometry approach in Rayleigh-lognormal fading. We present a geometric model of cognitive radio networks where primary transmitters, primary receivers, secondary transmitters, and secondary receivers are distributed as a Poisson point process. We analytically derive the coverage probability and transmission rate of that network. Moreover, we obtain closed-form expressions of coverage probability and transmission rate. We then numerically evaluate coverage probability and transmission rate performance. It is shown that for the coverage probability and transmission rate, the results are better for lower densities of primary transmitters and secondary transmitters.

Energy efficiency analysis of cognitive radio network using stochastic geometry

We investigate the energy efficiency with the relation of area spectral efficiency of a cognitive radio network using stochastic geometry approach. Network coverage probabilities are derived for the interference of cognitive transmitters and primary transmitters, with consideration of two important parameters: probability of ideal channel and probability of transmission schedule. Furthermore, we formulate the energy efficiency of this network for both perfect and imperfect detection of primary users and cognitive users. For this energy efficiency analysis, a constant base station power consumption model is used, and network power consumption is taken into account. The probabilities of ideal channel and transmission schedule are crucial parameters which affect both coverage probability and energy efficiency. Simulation results demonstrate that higher probabilities of ideal channel and transmission schedule are significantly more energy efficient than lower probabilities.

Outage and energy-efficiency analysis of cognitive radio networks: A stochastic approach to transmit antenna selection

Cognitive radio networks have recently attracted significant research attention owing to their promise for application in future cellular communication. In this light, given the intense power consumption of wireless networks, considerable research is now being directed at designing random cognitive radio networks with enhanced energy efficiency. In this study, we investigate the outage probability and energy efficiency in a cognitive radio network, modeling the locations of the primary users and cognitive users as a Poisson point process. We derive closed-form expressions for the outage probability and energy efficiency with consideration of the probabilities of unoccupied (not utilized by the primary users) channel selection and successful transmission for imperfect detection in an interference-limited environment of cognitive radio network. Furthermore, we propose a transmit antenna selection method for the cognitive transmitter in such networks and accordingly develop closed-form expressions for the outage probability and energy efficiency. The study reported here highlights the importance of combining the capabilities of unoccupied channel selection and successful transmission in cognitive radio networks to achieve optimal performance regarding outage probability and energy efficiency. In terms of energy efficiency, there is an optimal threshold that maximizes the energy efficiency. For implementation in transmit antenna selection, the outage probability can be significantly decreased by increasing the number of transmit antennas, even though the energy efficiency is maximized at the target outage probability.