Open Loop vs Closed Loop MIMO in LTE

MIMO technology is one of the most impactful innovations introduced in LTE to meet the ever-growing demand for higher data rates, improved spectrum efficiency, and enhanced network capacity. By leveraging multiple antennas at both the transmitter (eNodeB) and the receiver (UE), MIMO systems exploit the spatial dimension of the wireless channel to simultaneously transmit and receive multiple data streams.

The principle behind MIMO is rooted in multipath propagation — a natural phenomenon in which transmitted signals arrive at the receiver via multiple paths due to reflection, diffraction, and scattering. In traditional single-antenna systems, multipath was often considered a source of interference and fading. However, MIMO turns multipath into an advantage by using sophisticated signal processing techniques to separate and combine these multiple paths, thereby improving link robustness and overall throughput.

In LTE, MIMO serves three primary purposes:

1. Spatial Multiplexing – Sending independent data streams over multiple antennas to increase data rate without consuming extra spectrum.
2. Transmit Diversity – Transmitting redundant copies of the same data over multiple antennas to combat fading and improve reliability.
3. Beamforming – Steering signals toward specific users to maximize the Signal-to-Interference-plus-Noise Ratio (SINR) and reduce inter-user interference.

To adapt to varying mobility conditions, channel characteristics, and network requirements, LTE supports two broad MIMO operation modes:

• Open Loop MIMO-Transmission without relying on detailed channel state feedback from the UE.
• Closed Loop MIMO-Transmission adapted based on precoding feedback from the UE.

Although both modes leverage multiple antennas and LTE’s predefined precoding codebooks (as defined in 3GPP TS 36.211 and 36.213), they differ in how much Channel State Information (CSI) is used by the transmitter and how precoding decisions are made.

• Open Loop MIMO operates without requiring instantaneous CSI feedback from the UE, making it more robust in rapidly changing channels but less optimal in static or slowly varying environments.
• Closed Loop MIMO relies on detailed CSI feedback (including Rank Indicator (RI), Precoding Matrix Indicator (PMI), and Channel Quality Indicator (CQI)) from the UE to dynamically adjust transmission parameters, enabling higher spectral efficiency when the channel is relatively stable.

Open Loop MIMO in LTE

Open Loop MIMO in LTE refers to transmission schemes where the eNodeB does not rely on instantaneous channel state information (CSI) from the UE for precoder selection.

Instead of adapting the precoder based on real-time feedback, the eNodeB:

• Uses Rank Adaptation derived from the Rank Indicator (RI) reported by the UE.
• Applies semi-static precoding matrices selected from a predefined LTE codebook, typically cycled over time.
• Employs transmit diversity schemes to improve robustness.

This approach reduces dependence on frequent feedback and is therefore more resilient to rapidly changing channel conditions.

Scenarios Where Open Loop MIMO is Used

Open Loop MIMO is preferred in situations where feedback-based adaptation is either unreliable or impractical, such as:

• High mobility scenarios – e.g., users in high-speed trains, where CSI feedback becomes outdated before it can be applied.
• Low SINR conditions – where achieving diversity gain is more important than maximizing multiplexing gain.
• Initial transmission stages – before accurate channel feedback is available from the UE.

Techniques Used in Open Loop

Two primary techniques are implemented under Open Loop MIMO in LTE:

1. Transmit Diversity-Achieved using Space-Frequency Block Coding (SFBC) to improve signal robustness without requiring channel feedback.
2. Open Loop Spatial Multiplexing-Uses precoder cycling across subframes from the LTE codebook, without adapting to instantaneous channel conditions.

Example

Consider a UE operating with Rank = 2:

• The eNodeB cycles through fixed precoders from the LTE codebook every few subframes.
• PMI feedback from the UE is not used in the selection process.

Effect:

• Performs well in channels with rapid variations where feedback would quickly become outdated.
• However, in stable channel conditions, it generally provides lower throughput compared to closed loop MIMO, which can adapt more precisely to channel characteristics.

Closed Loop MIMO in LTE

Closed Loop MIMO in LTE is a transmission scheme where the eNodeB dynamically adapts its precoding strategy based on real-time channel state information (CSI) provided by the UE.

In this mode, the UE continuously measures the downlink channel characteristics using Cell-specific Reference Signals (CRS) or Channel State Information Reference Signals (CSI-RS). Based on these measurements, the UE feeds back three key parameters to the eNodeB:

• Rank Indicator (RI) → Specifies the optimal number of spatial layers (data streams) the eNodeB should transmit.
• Precoding Matrix Indicator (PMI) → Identifies the precoding matrix from LTE’s standardized codebook that best matches the current channel conditions.
• Channel Quality Indicator (CQI) → Suggests the highest MCS the channel can support while maintaining the target BLER.

By using these feedback reports, the eNodeB can align its transmission strategy to the instantaneous channel state, improving throughput and efficiency.

Scenarios Where Closed Loop MIMO is Used

Closed Loop MIMO is particularly beneficial when:

• Mobility is low to medium → Feedback remains valid long enough for the eNodeB to adapt transmission.
• Channel conditions are stable → Allows for accurate and beneficial precoding adjustments.
• Signal-to-Interference-plus-Noise Ratio (SINR) is high → Enables the use of higher-order modulation and multiple spatial layers.
• The system’s goal is to maximize throughput rather than prioritize diversity robustness.

Techniques Used in Closed Loop

1. Single-User MIMO (SU-MIMO) with Optimal Precoding-The eNodeB transmits multiple spatial layers to a single UE using the PMI-selected precoder to maximize received SNR and minimize inter-layer interference.
2. Multi-User MIMO (MU-MIMO) with Interference-Aware Precoding-The eNodeB serves multiple UEs simultaneously on the same time-frequency resources, selecting precoders to minimize cross-user interference based on their respective PMI reports.

Example

Step-by-step operation:

Channel Estimation

• The UE uses CRS or CSI-RS to estimate the downlink channel matrix H.
• This matrix represents the complex gain between each transmit and receive antenna pair.

Optimal Precoder Computation

• Using the estimated channel H, the UE calculates the optimal precoding matrix W that maximizes the post-processing SNR or channel capacity.

Codebook Matching

• LTE defines a finite set of precoders in its codebook (per 3GPP TS 36.211).
• The UE finds the matrix from this set that most closely approximates W.

PMI Feedback

• The UE reports the PMI, along with RI and CQI, over the uplink control channel (PUCCH) or shared channel (PUSCH).

Transmission Adaptation

• The eNodeB applies the selected PMI for subsequent downlink transmissions until updated feedback is received.

Effect:

• Advantage: In stable and predictable channel environments, closed loop MIMO can significantly increase throughput by aligning transmission with channel characteristics.
• Limitation: In high mobility scenarios, the feedback may become outdated, leading to suboptimal performance compared to open loop MIMO.

Aspect	Open Loop MIMO	Closed Loop MIMO
Feedback Parameters	RI, CQI only	RI, CQI, PMI
Precoding Selection	Fixed or semi-random precoder cycling from LTE codebook	Selected adaptively based on PMI feedback
Channel State Information (CSI) Dependency	Low – does not rely on instantaneous CSI	High – relies on real-time CSI from UE
Adaptability to Fast Fading	High – unaffected by feedback delay	Lower – performance degrades if channel changes faster than feedback update
Performance in Stable Channels	Lower throughput compared to closed loop	Higher throughput by aligning transmission to channel
Mobility Suitability	Best for high mobility (e.g., high-speed trains)	Best for low to medium mobility
Complexity	Lower – simpler transmitter implementation	Higher – requires CSI estimation and feedback processing
Robustness to CSI Errors	High – not dependent on CSI accuracy	Lower – wrong PMI leads to degraded performance
Typical Use Cases	Initial transmissions, high mobility, poor channel conditions	Stationary or slow-moving UEs, high SINR, capacity-focused deployments
Example Technique	Transmit Diversity (SFBC), Open Loop Spatial Multiplexing	SU-MIMO, MU-MIMO with interference-aware precoding

Open Loop and Closed Loop MIMO are two LTE transmission modes that differ in how they use channel state information (CSI) from the UE. Open Loop MIMO relies on rank adaptation and precoder cycling without instantaneous CSI, making it robust in high mobility and rapidly changing channels, though with lower throughput in stable conditions. Closed Loop MIMO uses UE feedback—Rank Indicator (RI), Precoding Matrix Indicator (PMI), and Channel Quality Indicator (CQI)—to adapt transmission in real time, achieving higher throughput in low to medium mobility with stable channels, but performance may degrade in fast-fading environments. Each approach serves distinct mobility, channel, and performance requirements in LTE deployments.

References

• 3GPP TS 36.211 – Physical Channels and Modulation, defines LTE MIMO modes, codebooks, and reference signals.
• 3GPP TS 36.212 – Multiplexing and Channel Coding, details RI, CQI, and PMI uplink reporting.
• 3GPP TS 36.213 – Physical Layer Procedures, explains PMI reporting, RI adaptation, and CQI feedback.
• Sesia, S. et al., LTE – The UMTS Long Term Evolution, Wiley, explains open vs closed loop MIMO operation.
• Dahlman, E. et al., 4G, LTE-Advanced Pro and The Road to 5G, Academic Press, covers LTE MIMO deployment trade-offs.
• Holma, H. & Toskala, A., LTE Advanced: 3GPP Solution for IMT-Advanced, Wiley, details LTE-Advanced MIMO enhancements.
• Myung, H. G. et al., “Single Carrier FDMA for Uplink Wireless Transmission,” IEEE VTM, explains channel estimation concepts.
• Rappaport, T. S., Wireless Communications: Principles and Practice, Prentice Hall, covers MIMO fundamentals and fading effects.