439 research outputs found
Uplink Non-Orthogonal Multiple Access with Finite-Alphabet Inputs
This paper focuses on the non-orthogonal multiple access (NOMA) design for a
classical two-user multiple access channel (MAC) with finite-alphabet inputs.
We consider practical quadrature amplitude modulation (QAM) constellations at
both transmitters, the sizes of which are assumed to be not necessarily
identical. We propose to maximize the minimum Euclidean distance of the
received sum-constellation with a maximum likelihood (ML) detector by adjusting
the scaling factors (i.e., instantaneous transmitted powers and phases) of both
users. The formulated problem is a mixed continuous-discrete optimization
problem, which is nontrivial to resolve in general. By carefully observing the
structure of the objective function, we discover that Farey sequence can be
applied to tackle the formulated problem. However, the existing Farey sequence
is not applicable when the constellation sizes of the two users are not the
same. Motivated by this, we define a new type of Farey sequence, termed punched
Farey sequence. Based on this, we manage to achieve a closed-form optimal
solution to the original problem by first dividing the entire feasible region
into a finite number of Farey intervals and then taking the maximum over all
the possible intervals. The resulting sum-constellation is proved to be a
regular QAM constellation of a larger size. Moreover, the superiority of NOMA
over time-division multiple access (TDMA) in terms of minimum Euclidean
distance is rigorously proved. Furthermore, the optimal rate allocation among
the two users is obtained in closed-form to further maximize the obtained
minimum Euclidean distance of the received signal subject to a total rate
constraint. Finally, simulation results are provided to verify our theoretical
analysis and demonstrate the merits of the proposed NOMA over existing
orthogonal and non-orthogonal designs.Comment: Submitted for possible journal publicatio
Downlink Precoding for Massive MIMO Systems Exploiting Virtual Channel Model Sparsity
In this paper, the problem of designing a forward link linear precoder for
Massive Multiple-Input Multiple-Output (MIMO) systems in conjunction with
Quadrature Amplitude Modulation (QAM) is addressed. First, we employ a novel
and efficient methodology that allows for a sparse representation of multiple
users and groups in a fashion similar to Joint Spatial Division and
Multiplexing. Then, the method is generalized to include Orthogonal Frequency
Division Multiplexing (OFDM) for frequency selective channels, resulting in
Combined Frequency and Spatial Division and Multiplexing, a configuration that
offers high flexibility in Massive MIMO systems. A challenge in such system
design is to consider finite alphabet inputs, especially with larger
constellation sizes such as . The proposed methodology is next
applied jointly with the complexity-reducing Per-Group Processing (PGP)
technique, on a per user group basis, in conjunction with QAM modulation and in
simulations, for constellation size up to . We show by numerical results
that the precoders developed offer significantly better performance than the
configuration with no precoder or the plain beamformer and with
Radio resource allocation for uplink OFDMA systems with finite symbol alphabet inputs
In this paper, we consider the radio resource allocation problem for uplink orthogonal frequency-division multiple-access (OFDMA) systems. The existing algorithms have been derived under the assumption of Gaussian inputs due to its closed-form expression of mutual information. For the sake of practicality, we consider the system with finite symbol alphabet (FSA) inputs and solve the problem by capitalizing on the recently revealed relationship between mutual information and minimum mean square error (MMSE). We first relax the problem to formulate it as a convex optimization problem, and then, we derive the optimal solution via decomposition methods. The optimal solution serves as an upper bound on the system performance. Due to the complexity of the optimal solution, a low-complexity suboptimal algorithm is proposed. Numerical results show that the presented suboptimal algorithm can achieve performance very close to the optimal solution and that it outperforms the existing suboptimal algorithms. Furthermore, using our proposed algorithm, significant power saving can be achieved in comparison to the case when a Gaussian input is assumed
A Survey of Physical Layer Security Techniques for 5G Wireless Networks and Challenges Ahead
Physical layer security which safeguards data confidentiality based on the
information-theoretic approaches has received significant research interest
recently. The key idea behind physical layer security is to utilize the
intrinsic randomness of the transmission channel to guarantee the security in
physical layer. The evolution towards 5G wireless communications poses new
challenges for physical layer security research. This paper provides a latest
survey of the physical layer security research on various promising 5G
technologies, including physical layer security coding, massive multiple-input
multiple-output, millimeter wave communications, heterogeneous networks,
non-orthogonal multiple access, full duplex technology, etc. Technical
challenges which remain unresolved at the time of writing are summarized and
the future trends of physical layer security in 5G and beyond are discussed.Comment: To appear in IEEE Journal on Selected Areas in Communication
Wireless Information and Power Transfer in Communication Networks: Performance Analysis and Optimal Resource Allocation
Energy harvesting is considered as a prominent solution to supply the energy demand for low-power consuming devices and sensor nodes. This approach relinquishes the requirements of wired connections and regular battery replacements. This thesis analyzes the performance of energy harvesting communication networks under various operation protocols and multiple access schemes. Furthermore, since the radio frequency signal has energy, in addition to conveying information, it is also possible to power energy harvesting component while establishing data connectivity with information-decoding component. This leads to the concept of simultaneous wireless information and power transfer. The central goal of this thesis is to conduct a performance analysis in terms of throughput and energy eļ¬ciency, and determine optimal resource allocation strategies for wireless information and power transfer.
In the ļ¬rst part of the thesis, simultaneous transfer of information and power through wireless links to energy harvesting and information decoding components is studied considering ļ¬nite alphabet inputs. The concept of non-uniform probability distribution is introduced for an arbitrary input, and mathematical formulations that relate probability distribution to the required harvested energy level are provided. In addition, impact of statistical quality of service (QoS) constraints on the overall performance is studied, and power control algorithms are provided.
Next, power allocation strategies that maximize the system energy eļ¬ciency subject to peak power constraints are determined for fading multiple access channels. The impact of channel characteristics, circuit power consumption and peak power level on the node selection, i.e., activation of user equipment, and the corresponding optimal transmit power level are addressed. Initially, wireless information transfer only is considered and subsequently wireless power transfer is taken into account. Assuming energy harvesting components, two scenarios are addressed based on the receiver architecture, i.e, having separated antenna or common antenna for the information decoding and energy harvesting components. In both cases, optimal SWIPT power control policies are identiļ¬ed, and impact of the required harvested energy is analyzed.
The second line of research in this thesis focuses on wireless-powered communication devices that operate based on harvest-then-transmit protocol. Optimal time allocation for the downlink and uplink operation interval are identiļ¬ed formulating throughput maximization and energy-eļ¬ciency maximization problems. In addition, the performance gain among various types of downlink-uplink operation protocols is analyzed taking into account statistical QoS constraints.
Furthermore, the performance analysis of energy harvesting user equipment is extended to full-duplex wireless information and power transfer as well as cellular networks. In full-duplex operation, optimal power control policies are identiļ¬ed, and the signiļ¬cance of introducing non-zero mean component on the information-bearing signal is analyzed. Meanwhile, SINR coverage probabilities, average throughput and energy eļ¬ciency are explicitly characterized for wireless-powered cellular networks, and the impact of downlink SWIPT and uplink mmWave schemes are addressed.
In the ļ¬nal part of the thesis, energy eļ¬ciency is considered as the performance metric, and time allocation strategies that maximize energy eļ¬ciency for wireless powered communication networks with non-orthogonal multiple access scheme are determined. Low complex algorithms are proposed based on Dinkelbachās method. In addition, the impact of statistical QoS constraints imposed as limitations on the buļ¬er violation probabilities is addressed
- ā¦