In this paper, we consider a distributed one-hop wireless network with n pairs of transmitters and receivers. It is assumed that each transmitter/receiver node is only connected to k receiver/transmitter nodes which are defined as neighboring nodes. The channel between the neighboring nodes is assumed to be Rayleigh fading. The objective is to find the maximum achievable sum-rate of the network in the asymptotic case of n, k ¿ ¿. It is shown that the asymptotic throughput of the system scales as n log k/k. An opportunistic on-off scheduling is proposed and shown to be asymptotically throughput optimal.

In this paper, a downlink system in which a single-antenna base station communicates with k single antenna users over a time-correlated fading channel is considered. It is assumed that each receiver knows its own channel state, while the rate of the channel variation for all users and the corresponding initial fading gains are known to the base station. The average (per channel use) throughput of the system is studied by applying various adaptive signaling schemes. Assuming a large number of users in the system, it is shown that using a scheduling scheme in which the base station transmits to the user with the maximum initial fading gain, while using a fixed codeword length for all users, achieves the order of the maximum throughput. Moreover, an alternative scheduling scheme is proposed (by accounting for users' delays) and shown to achieve the optimum long-term fairness, while preserving the order of the maximum throughput.

In this paper, a MIMO Broadcast Channel (MIMO-BC) with large (K) number of users is considered. It is assumed that all users have a hard delay constraint D. We propose a scheduling algorithm for maximizing the throughput of the system, while satisfying the delay constraint for all users. It is proved that by using the proposed algorithm, it is possible to achieve the maximum throughput and maximum fairness in the network, simultaneously, in the asymptotic case of K rarr infin. We introduce a new performance metric in the network, called "minimum average throughput", and prove that the proposed algorithm is capable of maximizing the minimum average throughput in a MIMO-BC, in the asymptotic case of K rarr infin. Finally, it is established that the proposed algorithm reaches the boundaries of the capacity region and stability region of the network, simultaneously, in the asymptotic case of K rarr infin.

A simple signaling method for broadcast channels with multiple-transmit multiple-receive antennas is proposed. In this method, for each user, the direction in which the user has the maximum gain is determined. The best user in terms of the largest gain is selected. The corresponding direction is used as the modulation vector (MV) for the data stream transmitted to the selected user. The algorithm proceeds in a recursive manner where in each step, the search for the best direction is performed in the null space of the previously selected MVs. It is demonstrated that with the proposed method, each selected MV has no interference on the previously selected MVs. Dirty-paper coding is used to cancel the remaining interference. For the case that each receiver has one antenna, the presented scheme coincides with the known scheme based on Gram-Schmidt orthogonalization (QR decomposition). To analyze the performance of the scheme, an upper bound on the cumulative distribution function (CDF) of each subchannel is derived which is used to establish the diversity order and the asymptotic sum-rate of the scheme. It is shown that using fixed rate codebooks, the diversity order of the jth data stream, 1 les j les M, is equal to N(M - j + 1)(K - j + 1), where M, N, and K indicate the number of transmit antennas, the number of receive antennas, and the number of users, respectively. Furthermore, it is proven that the throughput of this scheme scales as M log log(K) and asymptotically (K rarr infin) tends to the sum-capacity of the multiple-input multiple-output (MIMO) broadcast channel. The simulation results indicate that the achieved sum-rate is close to the sum-capacity of the underlying broadcast channel.

In this paper, the diversity-multiplexing trade-off is derived for a one-dimensional equally-spaced Rayleigh fading ad-hoc network. It is assumed that the interference from each link to the other links in the network declines exponentially with the distance, such that the attenuation between two neighbor links is rhoalpha0. For any given multiplexing gain r, the maximum diversity gain is achieved by utilizing a general time-sharing scheme. We obtain an explicit formula for the maximum diversity gain, and show that depending on the value of r and alpha0, there is an optimum time-sharing factor which yields the maximum diversity gain.

The capacity of time-varying channels with periodic feedback at the transmitter is evaluated. It is assumed that the channel-state information (CSI) is perfectly known at the receiver and is fed back to the transmitter at the regular time intervals. The system capacity is investigated in two cases: 1) finite-state Markov channel, and 2) additive white Gaussian noise channel with time-correlated fading. In the first case, it is shown that the capacity is achievable by multiplexing multiple codebooks across the channel. In the second case, the channel capacity and the optimal adaptive coding is obtained. It is shown that the optimal adaptation can be achieved by a single Gaussian codebook, while adaptively allocating the total power based on the side information at the transmitter.

In this paper, a downlink scenario in which a single-antenna base station communicates with K single antenna users, over a time-correlated fading channel, is considered. It is assumed that channel state information is perfectly known at each receiver, while the statistical characteristics of the fading process and the fading gain at the beginning of each frame are known to the transmitter. By evaluating the random coding error exponent of the time-correlated fading channel, we show that there is an optimal codeword length which maximizes the throughput. We examine the throughput of the conventional scheduling that transmits to the user with the maximum signal to noise ratio using both fixed length codewords and variable length codewords. Although optimizing the codeword length improves the performance, it is shown that using the conventional scheduling, a gap of Omega(radiclog log log K) exists between the achievable throughput and the maximum possible throughput of the system. We propose a simple scheduling that considers both the signal to noise ratio and the channel time variation. We show that by using this scheduling, the gap between the achievable throughput and the maximum throughput of the system approaches zero

We study a multiple-input multiple-output (MIMO) wireless system where the channel state information is partially available at the transmitter through a feedback link. Based on singular value decomposition, the MIMO channel is split into independent sub-channels. Effective feedback of the required spatial channel information entails efficient quantization/encoding of a unitary matrix. We propose two schemes for quantizing unitary matrices via Givens rotations and examine the performance for a scenario where the rates allocated to the sub-channels are selected according to their corresponding gains. Numerical results show that the proposed schemes offer a significant performance improvement as compared to that of MIMO systems without feedback, with a negligible increase in the complexity.

In this work, we study a multiple-input multiple-output wireless system, where the channel state information is partially available at the transmitter through a feedback link. Based on singular value decomposition, the MIMO channel is split into independent subchannels, which allows separate, and therefore, efficient decoding of the transmitted data signal. Effective feedback of the required spatial channel information entails efficient quantization/encoding of a Haar unitary matrix. The parameter reduction of an n /spl times/ n unitary matrix to its n/sup 2/ - n basic parameters is performed through Givens decomposition. We prove that Givens matrices of a Haar unitary matrix are statistically independent. Subsequently, we derive the probability distribution function (PDF) of the corresponding matrix elements. Based on these analyses, an efficient quantization scheme is proposed. The performance evaluation is provided for a scenario where the rates allocated to each independent channel are selected according to its corresponding gain. The results indicate a significant performance improvement compared to the performance of MIMO systems without feedback at the cost of a very low-rate feedback link.