1,467 research outputs found
MmWave Massive MIMO Based Wireless Backhaul for 5G Ultra-Dense Network
Ultra-dense network (UDN) has been considered as a promising candidate for
future 5G network to meet the explosive data demand. To realize UDN, a
reliable, Gigahertz bandwidth, and cost-effective backhaul connecting
ultra-dense small-cell base stations (BSs) and macro-cell BS is prerequisite.
Millimeter-wave (mmWave) can provide the potential Gbps traffic for wireless
backhaul. Moreover, mmWave can be easily integrated with massive MIMO for the
improved link reliability. In this article, we discuss the feasibility of
mmWave massive MIMO based wireless backhaul for 5G UDN, and the benefits and
challenges are also addressed. Especially, we propose a digitally-controlled
phase-shifter network (DPSN) based hybrid precoding/combining scheme for mmWave
massive MIMO, whereby the low-rank property of mmWave massive MIMO channel
matrix is leveraged to reduce the required cost and complexity of transceiver
with a negligible performance loss. One key feature of the proposed scheme is
that the macro-cell BS can simultaneously support multiple small-cell BSs with
multiple streams for each smallcell BS, which is essentially different from
conventional hybrid precoding/combining schemes typically limited to
single-user MIMO with multiple streams or multi-user MIMO with single stream
for each user. Based on the proposed scheme, we further explore the fundamental
issues of developing mmWave massive MIMO for wireless backhaul, and the
associated challenges, insight, and prospect to enable the mmWave massive MIMO
based wireless backhaul for 5G UDN are discussed.Comment: This paper has been accepted by IEEE Wireless Communications
Magazine. This paper is related to 5G, ultra-dense network (UDN), millimeter
waves (mmWave) fronthaul/backhaul, massive MIMO, sparsity/low-rank property
of mmWave massive MIMO channels, sparse channel estimation, compressive
sensing (CS), hybrid digital/analog precoding/combining, and hybrid
beamforming. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=730653
Multiuser Precoding and Channel Estimation for Hybrid Millimeter Wave MIMO Systems
In this paper, we develop a low-complexity channel estimation for hybrid
millimeter wave (mmWave) systems, where the number of radio frequency (RF)
chains is much less than the number of antennas equipped at each transceiver.
The proposed channel estimation algorithm aims to estimate the strongest
angle-of-arrivals (AoAs) at both the base station (BS) and the users. Then all
the users transmit orthogonal pilot symbols to the BS via these estimated
strongest AoAs to facilitate the channel estimation. The algorithm does not
require any explicit channel state information (CSI) feedback from the users
and the associated signalling overhead of the algorithm is only proportional to
the number of users, which is significantly less compared to various existing
schemes. Besides, the proposed algorithm is applicable to both non-sparse and
sparse mmWave channel environments. Based on the estimated CSI, zero-forcing
(ZF) precoding is adopted for multiuser downlink transmission. In addition, we
derive a tight achievable rate upper bound of the system. Our analytical and
simulation results show that the proposed scheme offer a considerable
achievable rate gain compared to fully digital systems, where the number of RF
chains equipped at each transceiver is equal to the number of antennas.
Furthermore, the achievable rate performance gap between the considered hybrid
mmWave systems and the fully digital system is characterized, which provides
useful system design insights.Comment: 6 pages, accepted for presentation, ICC 201
Achievable Rates of Multi-User Millimeter Wave Systems with Hybrid Precoding
Millimeter wave (mmWave) systems will likely employ large antenna arrays at
both the transmitters and receivers. A natural application of antenna arrays is
simultaneous transmission to multiple users, which requires multi-user
precoding at the transmitter. Hardware constraints, however, make it difficult
to apply conventional lower frequency MIMO precoding techniques at mmWave. This
paper proposes and analyzes a low complexity hybrid analog/digital beamforming
algorithm for downlink multi-user mmWave systems. Hybrid precoding involves a
combination of analog and digital processing that is motivated by the
requirement to reduce the power consumption of the complete radio frequency and
mixed signal hardware. The proposed algorithm configures hybrid precoders at
the transmitter and analog combiners at multiple receivers with a small
training and feedback overhead. For this algorithm, we derive a lower bound on
the achievable rate for the case of single-path channels, show its asymptotic
optimality at large numbers of antennas, and make useful insights for more
general cases. Simulation results show that the proposed algorithm offers
higher sum rates compared with analog-only beamforming, and approaches the
performance of the unconstrained digital precoding solutions.Comment: to be presented in IEEE ICC 2015 - Workshop on 5G & Beyond - Enabling
Technologies and Application
Exploiting Interference Alignment in Multi-Cell Cooperative OFDMA Resource Allocation
This paper studies interference alignment (IA) based multi-cell cooperative
resource allocation for the downlink OFDMA with universal frequency reuse.
Unlike the traditional scheme that treats subcarriers as separate dimensions
for resource allocation, the IA technique is utilized to enable
frequency-domain precoding over parallel subcarriers. In this paper, the joint
optimization of frequency-domain precoding via IA, subcarrier user selection
and power allocation is investigated for a cooperative three-cell OFDMA system
to maximize the downlink throughput. Numerical results for a simplified
symmetric channel setup reveal that the IA-based scheme achieves notable
throughput gains over the traditional scheme only when the inter-cell
interference link has a comparable strength as the direct link, and the
receiver SNR is sufficiently large. Motivated by this observation, a practical
hybrid scheme is proposed for cellular systems with heterogenous channel
conditions, where the total spectrum is divided into two subbands, over which
the IAbased scheme and the traditional scheme are applied for resource
allocation to users located in the cell-intersection region and cellnon-
intersection region, respectively. It is shown that this hybrid resource
allocation scheme flexibly exploits the downlink IA gains for OFDMA-based
cellular systems.Comment: 5 pages, 5 figures, GC2011 conferenc
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