Multiple User Channels Research Articles

Joint Space-time Coding and Power Domain Non-orthogonal Multiple Access for Future Wireless System

According to information theory, non-orthogonal transmission can achieve the multiple-user channel capacity with an onion-peeling like successive interference cancellation (SIC) based detection followed by a capacity approaching channel code. However, in multiple antenna system, due to the unideal characteristic of the SIC detector, the residual interference propagated to the next detection stage will significantly degrade the detection performance of spatial data layers. To overcome this problem, we proposed a modified power-domain non-orthogonal multiple access (P-NOMA) scheme joint designed with space-time coding for multiple input multiple output (MIMO) NOMA system. First, with proper power allocation for each user, inter-user signals can be separated from each other for NOMA detection. Second, a well-designed quasi-orthogonal space-time block code (QO-STBC) was employed to facilitate the SIC-based MIMO detection of spatial data layers within each user. Last, we proposed an optimization algorithm to assign channel coding rates to balance the bit error rate (BER) performance of those spatial data layers for each user. Link-level performance simulation results demonstrate that the proposed time-space-power domain joint transmission scheme performs better than the traditional P-NOMA scheme. Furthermore, the proposed algorithm is of low complexity and easy to implement.

Low Complexity Beamforming and User Selection Schemes for 5G MIMO-NOMA Systems

This paper investigates the resource allocation (RA) problem for the downlink multiple input multiple output-based non-orthogonal multiple access (MIMO-NOMA) system, which is usually solved through a beamforming (BF) process and a user selection (US) process. In this paper, we propose the multiple-user channel state information (CSI)-based singular value decomposition (MU-CSI-SVD) BF scheme and the minimization of power (Min-Power) US scheme. Under perfect CSI scenarios, the proposed MU-CSI-SVD achieves near optimal sum rate performance with the high-complexity BF scheme while has the same level computational complexity as the low-complexity BF scheme. For imperfect CSI scenarios, the proposed MU-CSI-SVD also achieves better outage probability performance but requires the same level computational complexity as the existing low-complexity BF scheme. Moreover, MU-CSI-SVD is helpful to decrease the computational complexity for solving the Min-Power US problem. Compared with existing US schemes, the proposed Min-Power scheme can achieve larger sum rate or lower outage probability with limited computational complexity increment. Therefore, in this paper, we develop a complete RA scheme for 5G MIMO-NOMA systems, which has excellent performance while with low computational complexity for both perfect and imperfect CSI scenarios.

Paranoid Secondary: Waterfilling in a Cognitive Interference Channel with Partial Knowledge

We study a two-user cognitive channel, where the primary flow is sporadic, cannot be re-designed and operating below its link capacity. To study the impact of primary traffic uncertainty, we propose a block activity model that captures the random on-off periods of primary's transmissions. Each block in the model can be split into parallel Gaussian-mixture channels, such that each channel resembles a multiple user channel (MAC) from the point of view of the secondary user. The secondary senses the current state of the primary at the start of each block. We show that the optimal power transmitted depends on the sensed state and the optimal power profile is paranoid, i.e. either growing or decaying in power as a function of time. We show that such a scheme achieves capacity when there is no noise in the sensing. The optimal transmission for the secondary performs rate splitting and follows a layered water-filling power allocation for each parallel channel to achieve capacity. The secondary rate approaches a genie-aided scheme for large block-lengths. Additionally, if the fraction of time primary uses the channel tends to one, the paranoid scheme and the genie-aided upper bound get arbitrarily close to a no-sensing scheme.

Achieving near-capacity at low SNR on a multiple-antenna multiple-user channel

We analyze the sensitivity of the capacity of a multi-antenna multi-user system to the number of users being served. We show analytically that, for a given desired sum-rate, the extra power needed to serve a subset of the users at low SNR (signal-to-noise ratio) can be very small, and is generally much smaller than the extra power needed to serve the same subset at high SNR. The advantages of serving only subsets of the users are many: multi-user algorithms have lower complexity, reduced channel-state information requirements, and, often, better performance. We provide guidelines on how many users to serve to get near-capacity performance with low complexity. For example, we show how in an eight-antenna eight-user system we can serve only four users and still be approximately 2 dB from capacity at very low SNR.

Reduced-rank channel estimation for time-slotted mobile communication systems

In time-slotted mobile communication systems with antenna array at the receiver, the space-time channel matrix is conventionally estimated by transmitting pilot symbols within each data packet (or block). This work is focused on reduced rank (RR) estimation methods that exploit the low-rank property of the space-time channel matrix to estimate single or multiple user channels from the observation of single or multiple training blocks. The proposed RR methods allow to improve the estimate accuracy by reducing the set of unknown parameters (rank reduction) and extending the training set (multiblock processing). The maximum likelihood RR estimate is obtained as the projection of the prewhitened full-rank (FR) estimate onto the spatial or temporal signal subspace. The paper shows that, even for time varying channels, these subspaces can be considered to be slowly varying, and therefore, they can be estimated with increased accuracy by properly exploiting training signals from several blocks. The analytical and numerical performance in terms of mean square error for the RR estimate shows that the main advantage of the proposed method with respect to the conventional FR one can be ascribed to the reduced complexity of the channel parameterization.

Discrimination Against Partially Overlapping Interference--Its Effect on Throughput in Frequency-Hopped Multiple Access Channels

In this paper we derive the probability of correct packet reception and the resulting channel throughput achievable in an asynchronous slow-frequency-hopped multiple user channel. Reed-Solomon coding is used to correct errors caused by other-user interference in an otherwise noiseless channel. We analyze and evaluate an M -ary FSK signaling scheme, which permits the discrimination against interfering signals that are present for a sufficiently small fraction of the hop duration, and results in substantial increases in channel throughput over previous models.

The capacity region of general multiple-access channel with certain correlated sources

A study of a class of multiple-user channels including general multiple-access channels with many correlated sources and many simultaneous receivers is presented. The main result is summarized as Theorems 4.1 and 5.1 which establish a simple characterization of the capacity region on the basis of the polymatroidal structure of a set of (conditional) mutual informations. The results include, as special cases, the Slepian and Wolf's result (1973) as well as Ulrey's (1975) . These may be regarded as further developments along the line shown by Ahlswede (1971) and Liao (1972) . Furthermore, a finite upper bound for the cardinalities of the ranges of auxiliary variables is given in Theorems 4.2 and 5.2. Finally, the relation between Slepian—Wolf's formalism and ours is clarified.