The performance of the uplink physical channel of the 3GPP LTE system is considered in this paper. Assuming a single user spatial division multiple access transmission scheme, where users' signals are transmitted over different subcarriers, a low complexity channel estimation technique is proposed for the physical uplink shared channel (PUSCH). The proposed channel estimation technique is shown to have significant gains in performance compared to other well known channel estimation techniques such as the maximum-likelihood (ML) and the inverse fast Fourier transform (IFFT) channel estimation methods [5]. Simulation results for different channel models and modulation and coding schemes (MCS) using incremental redundancy (IR) based hybrid automatic repeat request (HARQ) operation are also shown. Finally, a robust detection scheme is proposed for the physical uplink control channel (PUCCH) and simulation results are summarized.

In this paper, we consider the downlink of a multiuser wireless communication system with multiple antennas at the base station and users each with a single receive antenna. It is known that when channel state information (CSI) is available at the transmitter a large performance gain can be achieved. In a system employing time-division duplexing (TDD), CSI can be obtained at the base station if there is reciprocity between the forward and reverse channels. CSI can also be conveyed from the users to the base station via a limited-rate feedback channel in a frequency-division duplexing (FDD) system. In any case, channel estimation errors are inevitable due to the presence of background noise in the estimated signal and due to the finite number of feedback bits used in a limited-rate feedback system model. In this paper, we first consider the general case when partial CSI is available at the transmitter. We derive an MMSE based precoding technique that considers channel estimation errors as an integral part of the system design. Using rate-distortion theory and the generalized Lloyd vector quantization algorithm, we then specialize our results for the more practical limited-rate feedback system model. Compared to previously proposed precoding techniques such as channel inversion and regularized channel inversion, it is shown that the proposed precoding technique significantly improves the average bit error rate (BER) in the system. Furthermore, the performance of the proposed technique is investigated in the high signal-tonoise ratio (SNR) regime. It is shown that the proposed technique suffers from a ceiling effect that asymptotically limits the system performance.

We consider the downlink of a multiuser communication system with multiple antennas at the transmitter and at each receiver. A new transmission scheme that employs dirty-paper coding (DPC) with partial interference cancellation is proposed. It is shown that given any user ordering the achievable throughput is asymptotically optimal in the high signal-to-noise ratio (SNR) regime and for all values of the SNR it improves over the throughput of the zero-forcing dirty-paper coding (ZFDPC) scheme [1]. Due to its implementation complexity issues, we also consider a low complexity linear transmission scheme. A precoding technique where interference is canceled successively at the base station is proposed. In this case, users treat the partial interference at the receiver as an independent noise, and it is shown that compared to other linear transmission schemes such as the block-diagonalization (BD) and the zero-forcing schemes, the achievable throughput of the proposed precoding scheme is improved for all SNR values.

Multiple-input-multiple-output (MIMO) communication systems can provide large capacity gains over traditional single-input-single-output (SISO) systems and are expected to be a core technology of next generation wireless systems. Often, these capacity gains are achievable only with some form of adaptive transmission. In this paper, we study the capacity loss (defined as the rate loss in bits/s/Hz) of the MIMO wireless system when the covariance matrix of the transmitted signal vector is designed using a low rate feedback channel. For the MIMO channel, we find a bound on the ergodic capacity loss when random codebooks, generated from the uniform distribution on the complex unit sphere, are used to convey the second order statistics of the transmitted signal from the receiver to the transmitter. In this case, we find a closed-form expression for the ergodic capacity loss as a function of the number of bits fed back at each channel realization. These results show that the capacity loss decreases at least as O(2/sup -B/(2MMt-2)/) where B is the number of feedback bits, M/sub t/ is the number of transmit antennas, and M=min{M/sub r/,M/sub t/} where M/sub r/ is the number of receive antennas. In the high SNR regime, we present a new bound on the capacity loss that is tighter than the previously derived bound and show that the capacity loss decreases exponentially as a function of the number of feedback bits.

In this paper, a multiple-input multiple-output (MIMO) communication system employing a quantized feedback channel is considered. Because of their capacity gain benefits, MIMO communication systems are expected to be a core technology of next generation wireless systems. We study the capacity loss of such systems when the transmitted signal covariance matrix is designed using a low rate feedback channel. For the MIMO channel, we find a universal bound on the instantaneous capacity loss, and we derive a bound on the average capacity loss in the particular case when random codebooks, generated from the uniform distribution on the complex unit sphere, are used to design the transmitted signal covariance matrix. In this case, we find a closed-form expression for the capacity loss as a function of the number of feedback bits used at each channel realization, and it is that the capacity loss decreases exponentially as a function of the number of feedback bits